Weller, Adrian

118 publications

ICLR 2025 Can Large Language Models Understand Symbolic Graphics Programs? Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf

ICML 2025 Certification for Differentially Private Prediction in Gradient-Based Training Matthew Robert Wicker, Philip Sosnin, Igor Shilov, Adrianna Janik, Mark Niklas Mueller, Yves-Alexandre De Montjoye, Adrian Weller, Calvin Tsay

ICML 2025 Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese, Xiao Wang, Adrian Weller, Nicolas Papernot

NeurIPS 2025 From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization Shoaib Ahmed Siddiqui, Adrian Weller, David Krueger, Gintare Karolina Dziugaite, Michael Curtis Mozer, Eleni Triantafillou

TMLR 2025 Getting Aligned on Representational Alignment Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Christopher J Cueva, Erin Grant, Iris Groen, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine Hermann, Kerem Oktar, Klaus Greff, Martin N Hebart, Nathan Cloos, Nikolaus Kriegeskorte, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas O'Connell, Thomas Unterthiner, Andrew Kyle Lampinen, Klaus Robert Muller, Mariya Toneva, Thomas L. Griffiths

ICML 2025 Gridded Transformer Neural Processes for Spatio-Temporal Data Matthew Ashman, Cristiana Diaconu, Eric Langezaal, Adrian Weller, Richard E Turner

AAAI 2025 Learning Personalized Decision Support Policies Umang Bhatt, Valerie Chen, Katherine M. Collins, Parameswaran Kamalaruban, Emma Kallina, Adrian Weller, Ameet Talwalkar

ICLR 2025 Linear Transformer Topological Masking with Graph Random Features Isaac Reid, Kumar Avinava Dubey, Deepali Jain, William F Whitney, Amr Ahmed, Joshua Ainslie, Alex Bewley, Mithun George Jacob, Aranyak Mehta, David Rendleman, Connor Schenck, Richard E. Turner, René Wagner, Adrian Weller, Krzysztof Marcin Choromanski

NeurIPS 2025 Neural Mutual Information Estimation with Vector Copulas Yanzhi Chen, Zijing Ou, Adrian Weller, Michael U. Gutmann

NeurIPS 2025 PoE-World: Compositional World Modeling with Products of Programmatic Experts Wasu Top Piriyakulkij, Yichao Liang, Hao Tang, Adrian Weller, Marta Kryven, Kevin Ellis

ICLRW 2025 Representational Alignment Supports Effective Teaching Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore Sumers, Michalis Korakakis, Umang Bhatt, Mark K Ho, Joshua B. Tenenbaum, Bradley C. Love, Zachary Pardos, Adrian Weller, Thomas L. Griffiths

ICLR 2025 Variance-Reducing Couplings for Random Features Isaac Reid, Stratis Markou, Krzysztof Marcin Choromanski, Richard E. Turner, Adrian Weller

ICLR 2025 VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning Yichao Liang, Nishanth Kumar, Hao Tang, Adrian Weller, Joshua B. Tenenbaum, Tom Silver, Joao F. Henriques, Kevin Ellis

NeurIPS 2024 Approximately Equivariant Neural Processes Matthew Ashman, Cristiana Diaconu, Adrian Weller, Wessel Bruinsma, Richard E. Turner

ICMLW 2024 Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation Katherine M. Collins, Najoung Kim, Yonatan Bitton, Verena Rieser, Shayegan Omidshafiei, Yushi Hu, Sherol Chen, Senjuti Dutta, Minsuk Chang, Kimin Lee, Youwei Liang, Georgina Evans, Sahil Singla, Gang Li, Adrian Weller, Junfeng He, Deepak Ramachandran, Krishnamurthy Dj Dvijotham

ICLRW 2024 Confidential-DPproof : Confidential Proof of Differentially Private Training Ali Shahin Shamsabadi, Gefei Tan, Tudor Ioan Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller

ICLR 2024 Confidential-DPproof: Confidential Proof of Differentially Private Training Ali Shahin Shamsabadi, Gefei Tan, Tudor Ioan Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller

ICLR 2024 General Graph Random Features Isaac Reid, Krzysztof Marcin Choromanski, Eli Berger, Adrian Weller

NeurIPSW 2024 LLMs on Interactive Feature Collections with Implicit Look-Ahead Strategies Juyeon Heo, Vihari Piratla, Kyunghyun Lee, Hyonkeun Joh, Adrian Weller

NeurIPS 2024 Large Language Models Must Be Taught to Know What They Don’t Know Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson

ICMLW 2024 Learning Generative Population Models from Multiple Clinical Datasets via Probabilistic Programming João Loula, Katherine M. Collins, Ulrich Schaechtle, Joshua B. Tenenbaum, Adrian Weller, Feras Saad, Timothy J. O'Donnell, Vikash Mansinghka

AISTATS 2024 Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamas Sarlos, Thomas Weingarten, Adrian Weller

ICLR 2024 MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu

NeurIPSW 2024 Modulating Language Model Experiences Through Frictions Katherine M. Collins, Valerie Chen, Ilia Sucholutsky, Hannah Rose Kirk, Malak Sadek, Holli Sargeant, Ameet Talwalkar, Adrian Weller, Umang Bhatt

ICLR 2024 Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf

ICLR 2024 Repelling Random Walks Isaac Reid, Eli Berger, Krzysztof Marcin Choromanski, Adrian Weller

NeurIPSW 2023 AI for Mathematics: A Cognitive Science Perspective Cedegao Zhang, Katherine Collins, Adrian Weller, Joshua Tenenbaum

ICMLW 2023 Algorithms for Optimal Adaptation ofDiffusion Models to Reward Functions Krishnamurthy Dj Dvijotham, Shayegan Omidshafiei, Kimin Lee, Katherine M. Collins, Deepak Ramachandran, Adrian Weller, Mohammad Ghavamzadeh, Milad Nasr, Ying Fan, Jeremiah Zhe Liu

AAAI 2023 Approximating Full Conformal Prediction at Scale via Influence Functions Javier Abad Martinez, Umang Bhatt, Adrian Weller, Giovanni Cherubin

NeurIPS 2023 Certification of Distributional Individual Fairness Matthew Wicker, Vihari Piratla, Adrian Weller

ICLR 2023 Confidential-PROFITT: Confidential PROof of FaIr Training of Trees Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller

TMLR 2023 Continual Learning by Modeling Intra-Class Variation Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu

NeurIPS 2023 Controlling Text-to-Image Diffusion by Orthogonal Finetuning Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf

NeurIPS 2023 Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

NeurIPS 2023 Diffused Redundancy in Pre-Trained Representations Vedant Nanda, Till Speicher, John Dickerson, Krishna Gummadi, Soheil Feizi, Adrian Weller

AAAI 2023 Do Invariances in Deep Neural Networks Align with Human Perception? Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller

ICML 2023 Efficient Graph Field Integrators Meet Point Clouds Krzysztof Marcin Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Deepali Jain, Tamas Sarlos, Snigdha Chaturvedi, Adrian Weller

NeurIPSW 2023 Estimation of Concept Explanations Should Be Uncertainty Aware Vihari Piratla, Juyeon Heo, Sukriti Singh, Adrian Weller

ICLRW 2023 GeValDi: Generative Validation of Discriminative Models Vivek Palaniappan, Matthew Ashman, Katherine M. Collins, Juyeon Heo, Adrian Weller, Umang Bhatt

ICLR 2023 Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf

UAI 2023 Human-in-the-Loop Mixup Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley Love, Adrian Weller

ICML 2023 Is Learning Summary Statistics Necessary for Likelihood-Free Inference? Yanzhi Chen, Michael U. Gutmann, Adrian Weller

AISTATS 2023 Iterative Teaching by Data Hallucination Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf

NeurIPS 2023 Learning to Receive Help: Intervention-Aware Concept Embedding Models Mateo Espinosa Zarlenga, Katie Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik

UAI 2023 Mnemonist: Locating Model Parameters That Memorize Training Examples Ali Shahin Shamsabadi, Jamie Hayes, Borja Balle, Adrian Weller

AAAI 2023 On the Expressive Flexibility of Self-Attention Matrices Valerii Likhosherstov, Krzysztof Choromanski, Adrian Weller

UAI 2023 On the Informativeness of Supervision Signals Ilia Sucholutsky, Ruairidh M. Battleday, Katherine M. Collins, Raja Marjieh, Joshua Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, Thomas L. Griffiths

ICCV 2023 Pairwise Similarity Learning Is SimPLE Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf

NeurIPS 2023 Quasi-Monte Carlo Graph Random Features Isaac Reid, Krzysztof M Choromanski, Adrian Weller

ICLR 2023 Robust Explanation Constraints for Neural Networks Matthew Robert Wicker, Juyeon Heo, Luca Costabello, Adrian Weller

ICML 2023 Simplex Random Features Isaac Reid, Krzysztof Marcin Choromanski, Valerii Likhosherstov, Adrian Weller

ICMLW 2023 The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs Lance Ying, Katherine M. Collins, Megan Wei, Cedegao E. Zhang, Tan Zhi-Xuan, Adrian Weller, Joshua B. Tenenbaum, Lionel Wong

AAAI 2023 Towards More Robust Interpretation via Local Gradient Alignment Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon

AAAI 2023 Towards Robust Metrics for Concept Representation Evaluation Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik

NeurIPS 2023 Use Perturbations When Learning from Explanations Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

NeurIPSW 2023 Use Perturbations When Learning from Explanations Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

NeurIPS 2022 A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets Miri Zilka, Bradley Butcher, Adrian Weller

NeurIPS 2022 Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

NeurIPS 2022 Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frederic Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik

AAAI 2022 CrossWalk: Fairness-Enhanced Node Representation Learning Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman

AAAI 2022 Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates Dan Ley, Umang Bhatt, Adrian Weller

ICML 2022 From Block-Toeplitz Matrices to Differential Equations on Graphs: Towards a General Theory for Scalable Masked Transformers Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamas Sarlos, Adrian Weller, Thomas Weingarten

ICLR 2022 Hybrid Random Features Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller

ICML 2022 Measuring Representational Robustness of Neural Networks Through Shared Invariances Vedant Nanda, Till Speicher, Camila Kolling, John P Dickerson, Krishna Gummadi, Adrian Weller

AAAI 2022 On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf

IJCAI 2022 On the Utility of Prediction Sets in Human-AI Teams Varun Babbar, Umang Bhatt, Adrian Weller

NeurIPS 2022 Scalable Infomin Learning Yanzhi Chen, Weihao Sun, Yingzhen Li, Adrian Weller

ICLR 2022 SphereFace2: Binary Classification Is All You Need for Deep Face Recognition Yandong Wen, Weiyang Liu, Adrian Weller, Bhiksha Raj, Rita Singh

ECCV 2022 Structural Causal 3D Reconstruction Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf

CVPR 2022 Towards Principled Disentanglement for Domain Generalization Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing

AISTATS 2021 CWY Parametrization: A Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller

AISTATS 2021 Learning with Hyperspherical Uniformity Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller

ICML 2021 Debiasing a First-Order Heuristic for Approximate Bi-Level Optimization Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Q Davis, Adrian Weller

ICLR 2021 Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antoran, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato

NeurIPS 2021 Iterative Teaching by Label Synthesis Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller

CVPR 2021 Orthogonal Over-Parameterized Training Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller

ICLR 2021 Rethinking Attention with Performers Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, Adrian Weller

NeurIPS 2021 Robust Inverse Reinforcement Learning Under Transition Dynamics Mismatch Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Adrian Weller, Volkan Cevher

NeurIPS 2021 Sub-Linear Memory: How to Make Performers SLiM Valerii Likhosherstov, Krzysztof M Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller

IJCAI 2020 Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks Moein Khajehnejad, Ahmad Asgharian Rezaei, Mahmoudreza Babaei, Jessica Hoffmann, Mahdi Jalili, Adrian Weller

IJCAI 2020 Evaluating and Aggregating Feature-Based Model Explanations Umang Bhatt, Adrian Weller, José M. F. Moura

NeurIPS 2020 Ode to an ODE Krzysztof M Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani

ICML 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani

ICLRW 2020 Time Dependence in Non-Autonomous Neural ODEs Jared Quincy Davis, Krzysztof Choromanski, Vikas Sindhwani, Jake Varley, Honglak Lee, Jean-Jacques Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia

NeurIPSW 2019 Exploring Properties of the Deep Image Prior Andreas Kattamis, Tameem Adel, Adrian Weller

NeurIPS 2019 Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models Yunfei Teng, Wenbo Gao, François Chalus, Anna E Choromanska, Donald Goldfarb, Adrian Weller

AAAI 2019 One-Network Adversarial Fairness Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller

AISTATS 2019 Orthogonal Estimation of Wasserstein Distances Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamas Sarlos, Adrian Weller

UAI 2019 The Sensitivity of Counterfactual Fairness to Unmeasured Confounding Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva

ICML 2019 TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning Tameem Adel, Adrian Weller

JMLR 2019 Train and Test Tightness of LP Relaxations in Structured Prediction Ofer Meshi, Ben London, Adrian Weller, David Sontag

ICML 2019 Unifying Orthogonal Monte Carlo Methods Krzysztof Choromanski, Mark Rowland, Wenyu Chen, Adrian Weller

AAAI 2018 Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning Nina Grgic-Hlaca, Muhammad Bilal Zafar, Krishna P. Gummadi, Adrian Weller

ICML 2018 Blind Justice: Fairness with Encrypted Sensitive Attributes Niki Kilbertus, Adria Gascon, Matt Kusner, Michael Veale, Krishna Gummadi, Adrian Weller

ICML 2018 Bucket Renormalization for Approximate Inference Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin

ICML 2018 Discovering Interpretable Representations for Both Deep Generative and Discriminative Models Tameem Adel, Zoubin Ghahramani, Adrian Weller

AISTATS 2018 Gauged Mini-Bucket Elimination for Approximate Inference Sungsoo Ahn, Michael Chertkov, Jinwoo Shin, Adrian Weller

NeurIPS 2018 Geometrically Coupled Monte Carlo Sampling Mark Rowland, Krzysztof M Choromanski, François Chalus, Aldo Pacchiano, Tamas Sarlos, Richard E Turner, Adrian Weller

ICML 2018 Structured Evolution with Compact Architectures for Scalable Policy Optimization Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard Turner, Adrian Weller

AISTATS 2018 The Geometry of Random Features Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller

IJCAI 2017 Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller

AISTATS 2017 Conditions Beyond Treewidth for Tightness of Higher-Order LP Relaxations Mark Rowland, Aldo Pacchiano, Adrian Weller

NeurIPS 2017 From Parity to Preference-Based Notions of Fairness in Classification Muhammad Bilal Zafar, Isabel Valera, Manuel Rodriguez, Krishna Gummadi, Adrian Weller

ICML 2017 Lost Relatives of the Gumbel Trick Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller

NeurIPS 2017 The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings Krzysztof M Choromanski, Mark Rowland, Adrian Weller

NeurIPS 2017 Uprooting and Rerooting Higher-Order Graphical Models Mark Rowland, Adrian Weller

UAI 2016 Characterizing Tightness of LP Relaxations by Forbidding Signed Minors Adrian Weller

AISTATS 2016 Clamping Improves TRW and Mean Field Approximations Adrian Weller, Justin Domke

AISTATS 2016 Tightness of LP Relaxations for Almost Balanced Models Adrian Weller, Mark Rowland, David A. Sontag

ICML 2016 Train and Test Tightness of LP Relaxations in Structured Prediction Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David Sontag

ICML 2016 Uprooting and Rerooting Graphical Models Adrian Weller

UAI 2015 Bethe and Related Pairwise Entropy Approximations Adrian Weller

AISTATS 2015 Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs Adrian Weller

UAI 2014 Approximating the Bethe Partition Function Adrian Weller, Tony Jebara

NeurIPS 2014 Clamping Variables and Approximate Inference Adrian Weller, Tony Jebara

UAI 2014 Understanding the Bethe Approximation: When and How Can It Go Wrong? Adrian Weller, Kui Tang, Tony Jebara, David A. Sontag

AISTATS 2013 Bethe Bounds and Approximating the Global Optimum Adrian Weller, Tony Jebara

UAI 2013 On MAP Inference by MWSS on Perfect Graphs Adrian Weller, Tony Jebara