NeurIPSW 2020

211 papers

$k$-Simplex2Vec: A Simplicial Extension of Node2Vec Celia Hacker

0-Dimensional Homology Preserving Dimensionality Reduction with TopoMap Harish Doraiswamy, Julien Tierny, Paulo J.S. Silva, Luis Gustavo Nonato, Cláudio Silva

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A Bumpy Journey: Exploring Deep Gaussian Mixture Models Margot Selosse, Claire Gormley, Julien Jacques, Christophe Biernacki

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A Case for New Neural Networks Smoothness Constraints Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed

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A Deep Architecture for Log-Linear Models Simon Luo, Sally Cripps, Mahito Sugiyama

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A Framework for Differentiable Discovery of Graph Algorithms Hanjun Dai, Xinshi Chen, Yu Li, Xin Gao, Le Song

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A Seq2Seq Approach to Symbolic Regression Luca Biggio, Tommaso Bendinelli, Aurelien Lucchi, Giambattista Parascandolo

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A Step Towards Neural Genome Assembly Lovro Vrček, Petar Veličković, Mile Sikic

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A Study of Quality and Diversity in K+1 GANs Ilya Kavalerov, Wojciech Czaja, Rama Chellappa

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A Worrying Analysis of Probabilistic Time-Series Models for Sales Forecasting Seungjae Jung, Kyung-Min Kim, Hanock Kwak, Young-Jin Park

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Accounting for Human Learning When Inferring Human Preferences Harry Giles, Lawrence Chan

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AdaBelief Optimizer: Adapting Stepsizes by theBelief in Observed Gradients Juntang Zhuang, Tommy Tang, Sekhar Tatikonda, Nicha C Dvornek, Yifan Ding, Xenophon Papademetris, James s Duncan

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Adversarial Training for Predictive Tasks: Theoretical Analysis and Limitations in the Deterministic Case. Thibault Lesieur, Jérémie Messud, Issa Hammoud, Hanyuan Peng, Céline Lacombe, Paulien Jeunesse

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An Information-Geometric Distance on the Space of Tasks Yansong Gao, Pratik Anil Chaudhari

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Anatomically Constrained ResNets Exhibit Opponent Receptive Fields; so What? Ethan Harris, Daniela Mihai, Jonathon Hare

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Annealed Importance Sampling with Q-Paths Rob Brekelmans, Vaden Masrani, Thang D Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen

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Application of Topological Data Analysis to Delirium Detection Mari Kajitani, Ken Kobayashi, Yuichi Ike, Takehiko Yamanashi, Yuhei Umeda, Yoshimasa Kadooka, Gen Shinozaki

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Approximate Probabilistic Inference with Composed Flows Jay Whang, Erik Lindgren, Alex Dimakis

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Are Gradient-Based Saliency Maps Useful in Deep Reinforcement Learning? Matthias Rosynski, Frank Kirchner, Matias Valdenegro-Toro

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Assessing the Importance of Colours for CNNs in Object Recognition Aditya Singh, Alessandro Bay, Andrea Mirabile

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Bayesian Inference in Physics-Driven Problems with Adversarial Priors Dhruv V Patel, Deep Ray, Harisankar Ramaswamy, Assad Oberai

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Bayesian Neural Network Priors Revisited Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Ratsch, Richard E Turner, Mark van der Wilk, Laurence Aitchison

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Bifurcation Analysis Using Zigzag Persistence Sarah Tymochko, Elizabeth Munch, Firas Khasawneh

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Brain-Inspired Predictive Coding Dynamics Improve the Robustness of Deep Neural Networks Bhavin Choksi, Milad Mozafari, Callum Biggs O'May, B. Ador, Andrea Alamia, Rufin VanRullen

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Can Neural Networks Learn Persistent Homology Features? Guido Montufar, Nina Otter, Yu Guang Wang

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Causal Inductive Synthesis Corpus Zenna Tavares, Ria Das, Elizabeth Weeks, Kate Lin, Joshua B. Tenenbaum, Armando Solar-Lezama

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Cell Complex Neural Networks Mustafa Hajij, Kyle Istvan, Ghada Zamzmi

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Challenging Euclidean Topological Autoencoders Michael Moor, Max Horn, Karsten Borgwardt, Bastian Rieck

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Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics Yair Schiff, Payel Das, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy

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CNNs Efficiently Learn Long-Range Dependencies Timo Lüddecke, Alexander S Ecker

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COCO: Learning Strategies for Online Mixed-Integer Control Abhishek Cauligi, Preston Culbertson, Mac Schwager, Bartolomeo Stellato, Marco Pavone

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Comparing Distance Metrics on Vectorized Persistence Summaries Brittany Fasy, Yu Qin, Brian Summa, Carola Wenk

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Comparing Fisher Information Regularization with Distillation for DNN Quantization Prad Kadambi, Karthikeyan Natesan Ramamurthy, Visar Berisha

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Compressed Sensing with Approximate Priors via Conditional Resampling Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price

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Compressed Sensing with Invertible Generative Models and Dependent Noise Jay Whang, Qi Lei, Alex Dimakis

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Conceptualization and Framework of Hybrid Intelligence Systems Nikhil Prakash, Kory Wallace Mathewson

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Continuous and Interactive Factual Knowledge Learning in Verification Dialogues Sahisnu Mazumder, Bing Liu, Nianzu Ma, Shuai Wang

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Continuous Latent Search for Combinatorial Optimization Sergey Bartunov, Vinod Nair, Peter Battaglia, Tim Lillicrap

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CoRefi: A Crowd Sourcing Suite for Coreference Annotation Aaron Bornstein, Arie Cattan, Ido Dagan

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CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions Tayfun Ates, Muhammed Samil Atesoglu, Cagatay Yigit, Ilker Kesen, Mert Kobas, Erkut Erdem, Aykut Erdem, Tilbe Goksun, Deniz Yuret

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CUDA-Optimized Real-Time Rendering of a Foveated Visual System Elian Malkin, Arturo Deza, Tomaso A Poggio

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Curvature as an Organizing Principle of Mid-Level Visual Representation: A Semantic-Preference Mapping Approach Shi Pui Donald Li, Michael Bonner

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Decision-Aware Model Learning for Actor-Critic Methods: When Theory Does Not Meet Practice Ângelo Gregório Lovatto, Thiago Pereira Bueno, Denis Mauá, Leliane Nunes de Barros

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Deep Graph Mapper: Seeing Graphs Through the Neural Lens Cristian Bodnar, Cătălina Cangea, Pietro Liò

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Deep Learning for Plasma Tomography in Nuclear Fusion Diogo R. Ferreira, Pedro J. Carvalho

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Deep Learning Generalization and the Convex Hull of Training Sets Roozbeh Yousefzadeh

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Deep Learning Initialized Phase Retrieval Raunak Manekar, Zhong Zhuang, Kshitij Tayal, Vipin Kumar, Ju Sun

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Denoising Score-Matching for Uncertainty Quantification in Inverse Problems Zaccharie Ramzi, Benjamin Remy, Francois Lanusse, Jean-Luc Starck, Philippe Ciuciu

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Differentiable Programming for Piecewise Polynomial Functions Minsu Cho, Ameya Joshi, Xian Yeow Lee, Aditya Balu, Adarsh Krishnamurthy, Baskar Ganapathysubramanian, Soumik Sarkar, Chinmay Hegde

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Differentiable Top-$k$ with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

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DIME: An Information-Theoretic Difficulty Measure for AI Datasets Peiliang Zhang, Huan Wang, Nikhil Naik, Caiming Xiong, Richard Socher

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Discrete Planning with Neuro-Algorithmic Policies Marin Vlastelica Pogančić, Michal Rolinek, Georg Martius

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Disentangled Face Representations in Deep Generative Models and the Human Brain Paul Soulos, Leyla Isik

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Dreaming with ARC Andrzej Banburski, Anshula Gandhi, Simon Alford, Sylee Dandekar, Sang Chin, Tomaso A Poggio

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Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers Antoine Prouvost, Justin Dumouchelle, Lara Scavuzzo, Maxime Gasse, Didier Chételat, Andrea Lodi

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End-to-End Differentiable GANs for Text Generation Sachin Kumar, Yulia Tsvetkov

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Estimating Total Correlation with Mutual Information Bounds Pengyu Cheng, Weituo Hao, Lawrence Carin

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Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization Michal Lisicki, Arash Afkanpour, Graham W Taylor

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Evidential Reasoning with Expert-Guided Machine Learning Xueying Ding, Gopaljee Atulya, Aarti Singh, Alex Davis, Shane Fazzio

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Explanation Augmented Feedback in Human-in-the-Loop Reinforcement Learning Lin Guan, Mudit Verma, Sihang Guo, Ruohan Zhang, Subbarao Kambhampati

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Fit the Right NP-Hard Problem: End-to-End Learning of Integer Programming Constraints Anselm Paulus, Michal Rolinek, Vít Musil, Brandon Amos, Georg Martius

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Fragment Relation Networks for Geometric Shape Assembly Jinhwi Lee, Jungtaek Kim, Hyunsoo Chung, Jaesik Park, Minsu Cho

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From EM-Projections to Variational Auto-Encoder Tian Han, Jun Zhang, Ying Nian Wu

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Functorial Clustering via Simplicial Complexes Dan Shiebler

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Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang, Bin Dai, David Wipf, Jun Zhu

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Fuzzy C-Means Clustering for Persistence Diagrams Thomas Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh

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GalaxyTSP: A New Billion-Node Benchmark for TSP Iddo Drori, Brandon J Kates, William R. Sickinger, Anant Girish Kharkar, Brenda Dietrich, Avi Shporer, Madeleine Udell

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GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon

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Generalisation and the Geometry of Class Separability Dominic Belcher, Adam Prugel-Bennett, Srinandan Dasmahapatra

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Generative Tomography Reconstruction Matteo Ronchetti, Davide Bacciu

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Generator Surgery for Compressed Sensing Jung Yeon Park, Niklas Smedemark-Margulies, Mara Daniels, Rose Yu, Jan-Willem van de Meent, PAul HAnd

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Giotto-Tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration Guillaume Tauzin, Umberto Lupo, Lewis Tunstall, Julian Burella Perez, Matteo Caorsi, Wojciech Reise, Anibal Maximiliano Medina-Mardones, Alberto Dassatti, Kathryn Hess

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Graph Conditional Variational Models: Too Complex for Multiagent Trajectories? Yannick Rudolph, Ulf Brefeld, Uwe Dick

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Hotspot Identification for Mapper Graphs Ciara Frances Loughrey, Anna Jurek-Loughrey, Nick Orr, Pawel Dlotko

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How Does Task Structure Shape Representations in Deep Neural Networks? Kushin Mukherjee, Timothy T. Rogers

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Human Adversarial QA: Did the Model Understand the Paragraph? Prachi Shriram Rahurkar, Matthew Lyle Olson, Prasad Tadepalli

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Human-in-the-Loop Solution for Scoring Economic Development from Geospatial Data Sungwon Park, Donghyun Ahn, Sungwon Han, Eunji Lee, Danu Kim, Jeasurk Yang, Susang Lee, Sangyoon Park, Hyunjoo Yang, Jihee Kim, Meeyoung Cha

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Hypothesis Classes with a Unique Persistence Diagram Are NOT Nonuniformly Learnable Nicholas George Bishop, Thomas Davies, Long Tran-Thanh

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I’m Sorry for Your Loss: Spectrally-Based Audio Distances Are Bad at Pitch Joseph Turian, Max Henry

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Identifying and Interpreting Tuning Dimensions in Deep Networks Nolan Simran Dey, Eric Taylor, Bryan P. Tripp, Alexander Wong, Graham W Taylor

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Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

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Improving Learning to Branch via Reinforcement Learning Haoran Sun, Wenbo Chen, Hui Li, Le Song

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Independent Versus Truncated Finite Approximations for Bayesian Nonparametric Inference Tin D. Nguyen, Jonathan H. Huggins, Lorenzo Masoero, Lester Mackey, Tamara Broderick

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Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning Emilio Jorge, Hannes Eriksson, Christos Dimitrakakis, Debabrota Basu, Divya Grover

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Intermediate Layer Optimization for Inverse Problems Using Deep Generative Models Joseph Dean, Giannis Daras, Alex Dimakis

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Interpretable Phase Detection and Classification with Persistent Homology Gregory Loges, Alex Cole, Gary Shiu

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Investment vs. Reward in a Competitive Knapsack Problem Oren Neumann, Claudius Gros

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IReEn: Reverse-Engineering of Black-Box Functions via Iterative Neural Program Synthesis Hossein Hajipour, Mateusz Malinowski, Mario Fritz

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Is the Discrete VAE’s Power Stuck in Its Prior? Haydn Thomas Jones, Juston Moore

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It Doesn’t Get Better and Here’s Why: A Fundamental Drawback in Natural Extensions of UCB to Multi-Agent Bandits Udari Madhushani, Naomi Leonard

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Iterative VAE as a Predictive Brain Model for Out-of-Distribution Generalization Victor Boutin, Aimen Zerroug, Minju Jung, Thomas Serre

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K-Plex Cover Pooling for Graph Neural Networks Davide Bacciu, Alessio Conte, Roberto Grossi, Francesco Landolfi, Andrea Marino

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Know Where to Drop Your Weights: Towards Faster Uncertainty Estimation Akshatha Kamath, Dwaraknath Gnaneshwar, Matias Valdenegro-Toro

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Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach Maosen Zhang, Nan Jiang, Lei Li, Yexiang Xue

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Learning a Manifold from a Teacher’s Demonstrations Pei Wang, Arash Givchi, Patrick Shafto

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Learning a Metacognition for Object Perception Marlene Berke, Mario Belledonne, Julian Jara-Ettinger

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Learning Elimination Ordering for Tree Decomposition Problem Taras Khakhulin, Roman Schutski, Ivan Oseledets

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Learning for Integer-Constrained Optimization Through Neural Networks with Limited Training Zhou Zhou, Shashank Jere, Lizhong Zheng, Lingjia Liu

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Learning Joint Intensity in a Multivariate Poisson Process on Statistical Manifolds Simon Luo, Feng Zhou, Lamiae Azizi, Mahito Sugiyama

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Learning Lower Bounds for Graph Exploration with Reinforcement Learning Jorel Elmiger, Lukas Faber, Pankaj Khanchandani, Oliver Paul Richter, Roger Wattenhofer

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Learning Spectral Regularizations for Linear Inverse Problems Hartmut Bauermeister, Martin Burger, Michael Moeller

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Learning to Infer Run-Time Invariants from Source Code Vincent Josua Hellendoorn, Premkumar Devanbu, Alex Polozov, Mark Marron

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Learning to Sample MRI via Variational Information Maximization Cagan Alkan, Morteza Mardani, Shreyas Vasanawala, John M. Pauly

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Learning to Select Nodes in Bounded Suboptimal Conflict-Based Search for Multi-Agent Path Finding Taoan Huang, Bistra Dilkina, Sven Koenig

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Learning Translation Invariance in CNNs Valerio Biscione, Jeffrey Bowers

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Less Can Be More in Contrastive Learning Jovana Mitrovic, Brian McWilliams, Melanie Rey

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Leveraging Class Hierarchy for Code Comprehension Jiyang Zhang, Sheena Panthaplackel, Pengyu Nie, Junyi Jessy Li, Ray Mooney, Milos Gligoric

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Likelihood Ratio Exponential Families Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg

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Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski

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Local vs. Global Interpretations for NLP Nimrah Shakeel

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LUMAWIG: Un-Bottling the Bottleneck Distance for Zero Dimensional Persistence Diagrams at Scale Paul Samuel Ignacio, Jay-Anne Bulauan, David Uminsky

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Matching Through Embedding in Dense Graphs Nitish K Panigrahy, Prithwish Basu, Don Towsley

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Measuring Few-Shot Extrapolation with Program Induction Ferran Alet, Javier Lopez-Contreras, Joshua B. Tenenbaum, Tomas Perez, Leslie Pack Kaelbling

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MEME: Generating RNN Model Explanations via Model Extraction Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò

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Modeling Human Visual Search: A Combined Bayesian Searcher and Saliency mAP Approach for Eye Movement Guidance in Natural Scenes Melanie Sclar, Gaston Bujia, Sebastian Vita, Guillermo Solovey, Juan Esteban Kamienkowski

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Multi-Parameter Hierarchical Clustering and Beyond Alexander Rolle

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Multi-Parameter Persistent Homology Is Practical (Extended Abstract) Michael Kerber

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Multidimensional Persistence Module Classification via Lattice-Theoretic Convolutions Hans Matthew Riess, Jakob Hansen

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Multiple Hypothesis Testing with Persistent Homology Mikael Vejdemo-Johansson, Sayan Mukherjee

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Natural Images Are More Informative for Interpreting CNN Activations than State-of-the-Art Synthetic Feature Visualizations Judy Borowski, Roland Simon Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis, Matthias Bethge, Wieland Brendel

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Natural Reweighted Wake-Sleep Csongor Huba Varady, Riccardo Volpi, Luigi Malago, Nihat Ay

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NetReAct: Interactive Learning for Network Summarization Sorour E. Amiri, Bijaya Adhikari, John Wenskovitch, Alexander Rodriguez, Michelle Dowling, Christopher North, B. Aditya Prakash

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Neural Algorithms for Graph Navigation Aaron Zweig, Nesreen Ahmed, Theodore L. Willke, Guixiang Ma

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Neural Large Neighborhood Search Ravichandra Addanki, Vinod Nair, Mohammad Alizadeh

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Neural-Driven Multi-Criteria Tree Search for Paraphrase Generation Betty Fabre, Tanguy Urvoy, Jonathan Chevelu, Damien Lolive

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Noisy Neural Network Compression for Analog Storage Devices Berivan Isik, Kristy Choi, Xin Zheng, H.-S. Philip Wong, Stefano Ermon, Tsachy Weissman, Armin Alaghi

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Novel Topological Shapes of Model Interpretability Hendrik Jacob van Veen

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Oasis: ILP-Guided Synthesis of Loop Invariants Sahil Bhatia, Saswat Padhi, Nagarajan Natarajan, Rahul Sharma, Prateek Jain

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On the Benefits of Early Fusion in Multimodal Representation Learning George Barnum, Sabera J Talukder, Yisong Yue

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On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks Stephen Mussmann, Robin Jia, Percy Liang

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On the Surprising Similarities Between Supervised and Self-Supervised Models Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Matthias Bethge, Felix A. Wichmann, Wieland Brendel

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On the Topological Expressive Power of Neural Networks Giovanni Petri, António Leitão

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On the Utility of Active Instance Selection for Few-Shot Learning Pouya Pezeshkpour, Zhengli Zhao, Sameer Singh

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On-the-Fly Adaptation of Source Code Models Disha Shrivastava, Hugo Larochelle, Daniel Tarlow

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Oversampling Tabular Data with Deep Generative Models: Is It Worth the Effort? Ramiro Camino, Chris Hammerschmidt, Radu State

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Passive Encrypted IoT Device Fingerprinting with Persistent Homology Joe Collins, Michaela Iorga, Dmitry Cousin, David Chapman

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Perfect Density Models Cannot Guarantee Anomaly Detection Charline Le Lan, Laurent Dinh

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Permutation Invariant Networks to Learn Wasserstein Metrics Arijit Sehanobish, Neal G Ravindra, David van Dijk

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PHASE: PHysically-Grounded Abstract Social Events for Machine Social Perception Aviv Netanyahu, Tianmin Shu, Boris Katz, Andrei Barbu, Joshua B. Tenenbaum

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Pitfalls in Machine Learning Research: Reexamining the Development Cycle Stella Biderman, Walter Scheirer

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Power Posteriors Do Not Reliably Learn the Number of Components in a Finite Mixture Diana Cai, Trevor Campbell, Tamara Broderick

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Predictive Coding Feedback Results in Perceived Illusory Contours in a Recurrent Neural Network Zhaoyang Pang, Bhavin Choksi, Callum Biggs O'May, Rufin VanRullen

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Problems Using Deep Generative Models for Probabilistic Audio Source Separation Maurice Frank, Maximilian Ilse

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Quality Estimation & Interpretability for Code Translation Mayank Agarwal, Kartik Talamadupula, Stephanie Houde, Fernando Martinez, Michael Muller, John Richards, Steven Ross, Justin Weisz

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Quantifying Barley Morphology Using the Euler Characteristic Transform Erik J Amezquita, Michelle Quigley, Tim Ophelders, Jacob Landis, Elizabeth Munch, Daniel Chitwood, Daniel Koenig

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Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon Arridge, Bangti Jin

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Real-Time Visual Feedback for Educative Benchmark Creation : A Human-and-Metric-in-the-Loop Workflow Anjana Arunkumar, Swaroop Mishra, Bhavdeep Singh Sachdeva, Chitta Baral, Chris Bryan

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ReGAL: Rule-Generative Active Learning for Model-in-the-Loop Weak Supervision David Kartchner, Wendi Ren, Davi Nakajima An, Chao Zhang, Cassie Mitchell

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Regularization of Persistent Homology Gradient Computation Padraig Corcoran, Bailin Deng

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Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy Shashi Kant Gupta

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Reinforcement Learning with Efficient Active Feature Acquisition Haiyan Yin, Yingzhen Li, Sinno Pan, Cheng Zhang, Sebastian Tschiatschek

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Representing Partial Programs with Blended Abstract Semantics Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum, Armando Solar-Lezama

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Research Directions to Validate Topological Models of Multi-Dimensional Data Nello Blaser, Michael Aupetit

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Rethinking Deep Policy Gradients via State-Wise Policy Improvement Kai-Chun Hu, Ping-Chun Hsieh, Ting Han Wei, I-Chen Wu

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Rethinking Supervised Learning: Insights from Biological Learning and from Calling It by Its Name Alex Hernández-García

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Revisiting "Qualitatively Characterizing Neural Network Optimization Problems" Jonathan Frankle

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Risk Quantification in Deep MRI Reconstruction Vineet Edupuganti, Morteza Mardani, Shreyas Vasanawala, John M. Pauly

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Robust Active Learning Strategies for Model Variability José Mena Roldán, Matthias Gallé

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Sample Space Truncation on Boltzmann Machines Mahito Sugiyama, Koji Tsuda, Hiroyuki Nakahara

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SampleFix: Learning to Correct Programs by Efficient Sampling of Diverse Fixes Hossein Hajipour, Apratim Bhattacharyya, Mario Fritz

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SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing Tao Yu, Rui Zhang, Alex Polozov, Christopher Meek, Ahmed Hassan Awadallah

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Selective Classification Can Magnify Disparities Across Groups Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang

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Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering Ricky T. Q. Chen, Dami Choi, Lukas Balles, David Duvenaud, Philipp Hennig

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Semi-Supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu

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Sensory Complexity and Global Gain in a DCNN Codetermine Optimal Arousal State Lynn Katrina Annika Sörensen, Heleen A. Slagter, H. Steven Scholte, Sander Bohte

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Sheaf Neural Networks Jakob Hansen, Thomas Gebhart

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Simplicial 2-Complex Convolutional Neural Networks Eric Bunch, Qian You, Glenn Fung, Vikas Singh

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Simplicial Neural Networks Stefania Ebli, Michaël Defferrard, Gard Spreemann

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Software Language Comprehension Using a Program-Derived Semantics Graph Roshni Iyer, Yizhou Sun, Wei Wang, Justin Gottschlich

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Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser Zahra Kadkhodaie, Eero Peter Simoncelli

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Sparsifying Networks by Traversing Geodesics Guruprasad Raghavan, Matt Thomson

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Structure and Randomness in Planning and Reinforcement Learning Piotr Kozakowski, Piotr Januszewski, Konrad Czechowski, Łukasz Kuciński, Piotr Miłoś

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Task-Driven Learning of Contour Integration Responses in a V1 Model Salman Khan, Alexander Wong, Bryan P. Tripp

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Teaching the Machine to Explain Itself Using Domain Knowledge Vladimir Balayan, Pedro Saleiro, Catarina Belém, Ludwig Krippahl, Pedro Bizarro

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Teaspoon: A Comprehensive Python Package for Topological Signal Processing Audun D Myers, Melih Yesilli, Sarah Tymochko, Firas Khasawneh, Elizabeth Munch

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Temperature Scaling for Quantile Calibration Saiteja Utpala, Piyush Rai

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TF-Coder: Program Synthesis for Tensor Manipulations Kensen Shi, David Bieber, Rishabh Singh

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The Curious Case of Stacking Boosted Relational Dependency Networks Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan

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The Design and Development of Games with a Purpose for AI Systems Zahra Ashktorab, Casey Dugan, J. Johnson, Qian Pan, Wei Zhang

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The Representation of Object Drawings and Sketches in Deep Convolutional Neural Networks Johannes Singer, Katja Seeliger, Martin N Hebart

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The Reverse Turing Test for Evaluating Interpretability Methods on Unknown Tasks Ana Gonzalez, Anders Søgaard

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The Volume of Non-Restricted Boltzmann Machines and Their Double Descent Model Complexity Prasad Cheema, Mahito Sugiyama

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TimeSHAP: Explaining Recurrent Models Through Sequence Perturbations João Sousa, Pedro Saleiro, André F. Cruz, Mario A. T. Figueiredo, Pedro Bizarro

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Topo Sampler: A Topology Constrained Noise Sampling for GANs Adrish Dey, Sayantan Das

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Topological Convolutional Neural Networks Ephy Love, Benjamin Filippenko, Vasileios Maroulas, Gunnar E. Carlsson

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Topological Echoes of Primordial Physics in the Universe at Large Scales Alex Cole, Matteo Biagetti, Gary Shiu

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TOTOPO: Classifying Univariate and Multivariate Time Series with Topological Data Analysis Pilyugina Polina, Rodrigo Rivera-Castro, Evgeny Burnaev

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Toward a Generalization Metric for Deep Generative Models Hoang Thanh-Tung, Truyen Tran

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Towards Neurally Augmented ALISTA Freya Behrens, Jonathan Sauder, Peter Jung

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Towards Transferring Algorithm Configurations Across Problems Alberto Franzin, Thomas Stützle

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Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity Ioanna Maria Attarian, Brett D Roads, Michael Curtis Mozer

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Trust, but Verify: Model-Based Exploration in Sparse Reward Environments Konrad Czechowski, Tomasz Odrzygóźdź, Michał Izworski, Marek Zbysiński, Łukasz Kuciński, Piotr Miłoś

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Type-Driven Neural Programming by Example Kiara Grouwstra, Emile van Krieken

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Uncertainty-Driven Adaptive Sampling via GANs Thomas Sanchez, Igor Krawczuk, Zhaodong Sun, Volkan Cevher

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Understanding CNNs as a Model of the Inferior Temporal Cortex: Using Mediation Analysis to Unpack the Contribution of Perceptual and Semantic Features in Random and Trained Networks Anna Truzzi, Rhodri Cusack

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Understanding Generalization Through Visualizations W Ronny Huang, Zeyad Emam, Micah Goldblum, Liam H Fowl, J K Terry, Furong Huang, Tom Goldstein

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Unlocking Inverse Problems Using Deep Learning: Breaking Symmetries in Phase Retrieval Kshitij Tayal, Chieh-Hsin Lai, Raunak Manekar, Zhong Zhuang, Vipin Kumar, Ju Sun

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Usable Information and Evolution of Optimal Representations During Training Michael Kleinman, Daksh Idnani, Alessandro Achille, Jonathan Kao

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Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Geoff Pleiss, John Patrick Cunningham

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Using Topological Autoencoders as a Filtering Function for Global and Local Topology Filip Cornell

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Value Alignment Verification Daniel S. Brown, Jordan Schneider, Scott Niekum

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Variational (Gradient) Estimate of the Score Function in Energy-Based Latent Variable Models Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang

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Virtual Savant: Learning for Optimization Renzo Massobrio, Sergio Nesmachnow, Bernabé Dorronsoro

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Visual Representations Derived from Multiplicative Interactions Eric Elmoznino, Michael Bonner

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Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs Stefan Horoi, Jessie Huang, Guy Wolf, Smita Krishnaswamy

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Wasserstein Learning of Determinantal Point Processes Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes

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Weighting Vectors for Machine Learning: Numerical Harmonic Analysis Applied to Boundary Detection Eric Bunch, Daniel Dickinson, Jeffery Kline, Glenn Fung

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What More Can Entity Linking Do for Question Answering? Jordan Lee Boyd-Graber, Pedro Rodriguez, Naveen Janaki Raman

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Why Are Bootstrapped Deep Ensembles Not Better? Jeremy Nixon, Balaji Lakshminarayanan, Dustin Tran

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Witness Autoencoder: Shaping the Latent Space with Witness Complexes Simon Till Schönenberger, Anastasiia Varava, Vladislav Polianskii, Jen Jen Chung, Danica Kragic, Roland Siegwart

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XLVIN: eXecuted Latent Value Iteration Nets Andreea Deac, Petar Veličković, Ognjen Milinković, Pierre-Luc Bacon, Jian Tang, Mladen Nikolić

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