Cho, Kyunghyun

125 publications

ICLR 2025 $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun

NeurIPS 2025 AION-1: Omnimodal Foundation Model for Astronomical Sciences Liam Holden Parker, Francois Lanusse, Jeff Shen, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Thibaut Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Pierre Cornette, Keiya Hirashima, Geraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Kyunghyun Cho, Miles Cranmer, Shirley Ho

ICLR 2025 Aioli: A Unified Optimization Framework for Language Model Data Mixing Mayee F Chen, Michael Y. Hu, Nicholas Lourie, Kyunghyun Cho, Christopher Re

ICLRW 2025 Aioli: A Unified Optimization Framework for Language Model Data Mixing Mayee F Chen, Michael Y. Hu, Nicholas Lourie, Kyunghyun Cho, Christopher Re

ICLRW 2025 All-Atom Protein Generation with Latent Diffusion Amy X. Lu, Wilson Yan, Sarah A Robinson, Simon Kelow, Kevin K Yang, Vladimir Gligorijevic, Kyunghyun Cho, Richard Bonneau, Pieter Abbeel, Nathan C. Frey

ICLR 2025 Concept Bottleneck Language Models for Protein Design Aya Abdelsalam Ismail, Tuomas Oikarinen, Amy Wang, Julius Adebayo, Samuel Don Stanton, Hector Corrada Bravo, Kyunghyun Cho, Nathan C. Frey

ICLRW 2025 Cost-Efficient Continual Learning with Sufficient Exemplar Memory Dong Kyu Cho, Taesup Moon, Rumi Chunara, Kyunghyun Cho, Sungmin Cha

TMLR 2025 Deep Autoregressive Models as Causal Inference Engines Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho

NeurIPS 2025 Efficient Semantic Uncertainty Quantification in Language Models via Diversity-Steered Sampling Ji Won Park, Kyunghyun Cho

ICML 2025 Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks Angelica Chen, Samuel Don Stanton, Frances Ding, Robert G Alberstein, Andrew Martin Watkins, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Nathan C. Frey

ICLRW 2025 Generalizing to Any Diverse Distribution: Uniformity & Rebalancing Andreas Loukas, Karolis Martinkus, Edward Wagstaff, Kyunghyun Cho

NeurIPS 2025 Generative Property Enhancer: Implicit Guided Generation Through Conditional Density Estimation Pedro O. Pinheiro, Pan Kessel, Aya Abdelsalam Ismail, Sai Pooja Mahajan, Kyunghyun Cho, Saeed Saremi, Natasa Tagasovska

TMLR 2025 Hyperparameters in Continual Learning: A Reality Check Sungmin Cha, Kyunghyun Cho

TMLR 2025 Large-Scale Targeted Cause Discovery via Learning from Simulated Data Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun, Hyun Oh Song, Kyunghyun Cho

NeurIPS 2025 Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models Vlad Sobal, Wancong Zhang, Kyunghyun Cho, Randall Balestriero, Tim G. J. Rudner, Yann LeCun

NeurIPS 2025 NaturalReasoning: Reasoning in the Wild with 2.8m Challenging Questions Weizhe Yuan, Jane Yu, Song Jiang, Karthik Padthe, Yang Li, Dong Wang, Ilia Kulikov, Kyunghyun Cho, Yuandong Tian, Jason E Weston, Xian Li

ICLRW 2025 Orchestrating Tool Ecosystem of Drug Discovery with Intention-Aware LLM Agents Mingyu Derek Ma, Karina Zadorozhny, Jesse Swanson, Nathan C. Frey, Keunwoo Choi, Maksim Eremeev, Sabrina J Mielke, Wenmo Sun, Melody Liu, Jonathan Wickes, Vladimir Gligorijevic, Richard Bonneau, Henri Dwyer, Kyunghyun Cho, Stephen Ra

NeurIPS 2025 Predicting Partially Observable Dynamical Systems via Diffusion Models with a Multiscale Inference Scheme Rudy Morel, Francesco Pio Ramunno, Jeff Shen, Alberto Bietti, Kyunghyun Cho, Miles Cranmer, Siavash Golkar, Olexandr Gugnin, Geraud Krawezik, Tanya Marwah, Michael McCabe, Lucas Thibaut Meyer, Payel Mukhopadhyay, Ruben Ohana, Liam Holden Parker, Helen Qu, François Rozet, K.D. Leka, Francois Lanusse, David Fouhey, Shirley Ho

ICLRW 2025 Residue-Level Text Conditioning for Protein Language Model Mutation Effect Prediction Dan Berenberg, Nate Gruver, Alan Nawzad Amin, Peter Mørch Groth, Leo Chen, Harsh R. Srivastava, Pascal Notin, Debora Susan Marks, Andrew Gordon Wilson, Kyunghyun Cho, Richard Bonneau

AISTATS 2025 Semiparametric Conformal Prediction Ji Won Park, Kyunghyun Cho

ICLRW 2025 Stress-Testing Offline Reward-Free Reinforcement Learning: A Case for Planning with Latent Dynamics Models Vlad Sobal, Wancong Zhang, Kyunghyun Cho, Randall Balestriero, Tim G. J. Rudner, Yann LeCun

ICLRW 2025 Supervised Contrastive Block Disentanglement Taro Makino, Ji Won Park, Natasa Tagasovska, Takamasa Kudo, Paula Coelho, Heming Yao, Jan-Christian Huetter, Ana Carolina Leote, Burkhard Hoeckendorf, Stephen Ra, David Richmond, Kyunghyun Cho, Aviv Regev, Romain Lopez

NeurIPS 2025 Test Time Scaling for Neural Processes Hyungi Lee, Moonseok Choi, Hyunsu Kim, Kyunghyun Cho, Rajesh Ranganath, Juho Lee

TMLR 2025 Training Dynamics of Learning 3D-Rotational Equivariance Max W Shen, Ewa Nowara, Michael Maser, Kyunghyun Cho

NeurIPS 2025 Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation Sungmin Cha, Kyunghyun Cho

ICMLW 2024 $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun

NeurIPSW 2024 $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun

ICML 2024 BOtied: Multi-Objective Bayesian Optimization with Tied Multivariate Ranks Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho

TMLR 2024 Blind Biological Sequence Denoising with Self-Supervised Set Learning Nathan Hoyen Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho

ICMLW 2024 Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms Samuel Don Stanton, Robert G Alberstein, Nathan C. Frey, Andrew Martin Watkins, Kyunghyun Cho

ICLR 2024 Concept Bottleneck Generative Models Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho

ICMLW 2024 Cramming Protein Language Model Training in 24 GPU Hours Nathan C. Frey, Taylor Joren, Aya Abdelsalam Ismail, Allen Goodman, Richard Bonneau, Kyunghyun Cho, Vladimir Gligorijevic

NeurIPS 2024 Implicitly Guided Design with PropEn: Match Your Data to Follow the Gradient Nataša Tagasovska, Vladimir Gligorijević, Kyunghyun Cho, Andreas Loukas

NeurIPS 2024 Iterative Reasoning Preference Optimization Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston

NeurIPS 2024 Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-Modal Learning Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho

NeurIPSW 2024 LLMs Are Highly-Constrained Biophysical Sequence Optimizers Angelica Chen, Samuel Don Stanton, Robert G Alberstein, Andrew Martin Watkins, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Nathan C. Frey

TMLR 2024 Learning from Natural Language Feedback Angelica Chen, Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez

NeurIPS 2024 Multiple Physics Pretraining for Spatiotemporal Surrogate Models Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Parker, Ruben Ohana, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Geraud Krawezik, Francois Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

NeurIPS 2024 Non-Convolutional Graph Neural Networks. Yuanqing Wang, Kyunghyun Cho

NeurIPS 2024 Preference Learning Algorithms Do Not Learn Preference Rankings Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho

ICMLW 2024 Preference Learning Algorithms Do Not Learn Preference Rankings Angelica Chen, Sadhika Malladi, Lily H Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho

ICMLW 2024 Preference Learning Algorithms Do Not Learn Preference Rankings Angelica Chen, Sadhika Malladi, Lily H Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho

ICLR 2024 Protein Discovery with Discrete Walk-Jump Sampling Nathan C. Frey, Dan Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hotzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

ICML 2024 Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning Sungmin Cha, Kyunghyun Cho, Taesup Moon

ICML 2024 Self-Rewarding Language Models Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, Jason E Weston

ICLR 2024 Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L Leavitt, Naomi Saphra

ICML 2024 Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization Deokjae Lee, Hyun Oh Song, Kyunghyun Cho

TMLR 2024 Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho

ICLR 2023 A Non-Monotonic Self-Terminating Language Model Eugene Choi, Kyunghyun Cho, Cheolhyoung Lee

NeurIPS 2023 AbDiffuser: Full-Atom Generation of In-Vitro Functioning Antibodies Karolis Martinkus, Jan Ludwiczak, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hotzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas

NeurIPSW 2023 AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models Francois Lanusse, Liam Holden Parker, Siavash Golkar, Alberto Bietti, Miles Cranmer, Michael Eickenberg, Geraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

ICMLW 2023 Concept Bottleneck Generative Models Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho

TMLR 2023 Detecting Incidental Correlation in Multimodal Learning via Latent Variable Modeling Taro Makino, Yixin Wang, Krzysztof J. Geras, Kyunghyun Cho

ICLRW 2023 Emulating Radiation Transport on Cosmological Scales Using a Denoising U-Net Mosima Masipa, Sultan Hassan, Mario Santos, Kyunghyun Cho, Gabriella Contardo

NeurIPSW 2023 Identifying Regularization Schemes That Make Feature Attributions Faithful Julius Adebayo, Samuel Don Stanton, Simon Kelow, Michael Maser, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Stephen Ra, Nathan C. Frey

TMLR 2023 Latent State Models of Training Dynamics Michael Y. Hu, Angelica Chen, Naomi Saphra, Kyunghyun Cho

CLeaR 2023 Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev

ICLRW 2023 Learning Protein Family Manifolds with Smoothed Energy-Based Models Nathan C. Frey, Dan Berenberg, Joseph Kleinhenz, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

ICLR 2023 Linear Connectivity Reveals Generalization Strategies Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho, João Sedoc, Naomi Saphra

NeurIPSW 2023 Multiple Physics Pretraining for Physical Surrogate Models Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Geraud Krawezik, Francois Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

TMLR 2023 Predicting Out-of-Domain Generalization with Neighborhood Invariance Nathan Hoyen Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi

NeurIPS 2023 Protein Design with Guided Discrete Diffusion Nate Gruver, Samuel Stanton, Nathan Frey, Tim G. J. Rudner, Isidro Hotzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew G Wilson

ICMLW 2023 Protein Design with Guided Discrete Diffusion Nate Gruver, Samuel Don Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hotzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson

NeurIPSW 2023 Protein Discovery with Discrete Walk-Jump Sampling Nathan Frey, Dan Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hotzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Vladimir Gligorijevic, Saeed Saremi

ICML 2023 Towards Understanding and Improving GFlowNet Training Max W Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani

NeurIPSW 2023 xVal: A Continuous Number Encoding for Large Language Models Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles Cranmer, Geraud Krawezik, Francois Lanusse, Michael McCabe, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

NeurIPSW 2022 A Pareto-Optimal Compositional Energy-Based Model for Sampling and Optimization of Protein Sequences Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic

NeurIPSW 2022 Automated Protein Function Description for Novel Class Discovery Meet Barot, Vladimir Gligorijevic, Richard Bonneau, Kyunghyun Cho

ICML 2022 Characterizing and Overcoming the Greedy Nature of Learning in Multi-Modal Deep Neural Networks Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, Krzysztof J Geras

ICLR 2022 Chemical-Reaction-Aware Molecule Representation Learning Hongwei Wang, Weijiang Li, Xiaomeng Jin, Kyunghyun Cho, Heng Ji, Jiawei Han, Martin D. Burke

NeurIPS 2022 Generative Multitask Learning Mitigates Target-Causing Confounding Taro Makino, Krzysztof Geras, Kyunghyun Cho

NeurIPSW 2022 Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev

ICMLW 2022 Linear Connectivity Reveals Generalization Strategies Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho, João Sedoc, Naomi Saphra

NeurIPSW 2022 Mitigating Input-Causing Confounding in Multimodal Learning via the Backdoor Adjustment Taro Makino, Krzysztof J. Geras, Kyunghyun Cho

ICLRW 2022 Multi-Segment Preserving Sampling for Deep Manifold Sampler Dan Berenberg, Jae Hyeon Lee, Simon Kelow, Ji Won Park, Andrew Watkins, Richard Bonneau, Vladimir Gligorijevic, Stephen Ra, Kyunghyun Cho

NeurIPSW 2022 PropertyDAG: Multi-Objective Bayesian Optimization of Partially Ordered, Mixed-Variable Properties for Biological Sequence Design Ji Won Park, Samuel Don Stanton, Saeed Saremi, Andrew Martin Watkins, Henri Dwyer, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho

ICLRW 2022 Separating the World and Ego Models for Self-Driving Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun

ICML 2021 Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo B Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras

ICCVW 2021 Causal BERT: Improving Object Detection by Searching for Challenging Groups Cinjon Resnick, Or Litany, Amlan Kar, Karsten Kreis, James Lucas, Kyunghyun Cho, Sanja Fidler

ICLRW 2021 Evaluating Representations by the Complexity of Learning Low-Loss Predictors William F Whitney, Min Jae Song, David Brandfonbrener, Jaan Altosaar, Kyunghyun Cho

ICLR 2021 Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule Shuhei Kurita, Kyunghyun Cho

AAAI 2021 MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling Sean Welleck, Kyunghyun Cho

ICML 2021 Rissanen Data Analysis: Examining Dataset Characteristics via Description Length Ethan Perez, Douwe Kiela, Kyunghyun Cho

ICLRW 2021 Rissanen Data Analysis: Examining Dataset Characteristics via Description Length Ethan Perez, Douwe Kiela, Kyunghyun Cho

NeurIPS 2021 True Few-Shot Learning with Language Models Ethan Perez, Douwe Kiela, Kyunghyun Cho

JMLR 2020 A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks Owen Marschall, Kyunghyun Cho, Cristina Savin

ICLR 2020 Dynamics-Aware Embeddings William Whitney, Rajat Agarwal, Kyunghyun Cho, Abhinav Gupta

AAAI 2020 Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior Raphael Shu, Jason Lee, Hideki Nakayama, Kyunghyun Cho

AAAI 2020 Learning to Learn Morphological Inflection for Resource-Poor Languages Katharina Kann, Samuel R. Bowman, Kyunghyun Cho

ICLR 2020 Mixout: Effective Regularization to Finetune Large-Scale Pretrained Language Models Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang

AAAI 2020 Neural Machine Translation with Byte-Level Subwords Changhan Wang, Kyunghyun Cho, Jiatao Gu

ICLR 2020 Neural Text Generation with Unlikelihood Training Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston

ICLR 2020 The Break-Even Point on Optimization Trajectories of Deep Neural Networks Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof Geras

NeurIPS 2019 Can Unconditional Language Models Recover Arbitrary Sentences? Nishant Subramani, Samuel Bowman, Kyunghyun Cho

AAAI 2019 Classifier-Agnostic Saliency mAP Extraction Konrad Zolna, Krzysztof J. Geras, Kyunghyun Cho

NeurIPSW 2019 Continual Learning via Neural Pruning Siavash Golkar, Micheal Kagan, Kyunghyun Cho

ICLR 2019 DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder Xiaodong Gu, Kyunghyun Cho, Jung-Woo Ha, Sunghun Kim

NeurIPSW 2019 Evaluating Biological Plausibility of Learning Algorithms the Lazy Way Owen Marschall, Kyunghyun Cho, Cristina Savin

ICML 2019 Non-Monotonic Sequential Text Generation Sean Welleck, Kianté Brantley, Hal Daumé Iii, Kyunghyun Cho

ICLR 2018 Boundary Seeking GANs R Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho, Yoshua Bengio

ICLR 2018 Emergent Communication in a Multi-Modal, Multi-Step Referential Game Katrina Evtimova, Andrew Drozdov, Douwe Kiela, Kyunghyun Cho

ICLR 2018 Emergent Translation in Multi-Agent Communication Jason Lee, Kyunghyun Cho, Jason Weston, Douwe Kiela

NeurIPS 2018 Loss Functions for Multiset Prediction Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho

AAAI 2018 Search Engine Guided Neural Machine Translation Jiatao Gu, Yong Wang, Kyunghyun Cho, Victor O. K. Li

ICLR 2018 Unsupervised Neural Machine Translation Mikel Artetxe, Gorka Labaka, Eneko Agirre, Kyunghyun Cho

AAAI 2017 Query-Efficient Imitation Learning for End-to-End Simulated Driving Jiakai Zhang, Kyunghyun Cho

NeurIPS 2017 Saliency-Based Sequential Image Attention with Multiset Prediction Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang

NeurIPS 2016 End-to-End Goal-Driven Web Navigation Rodrigo Nogueira, Kyunghyun Cho

NeurIPS 2016 Iterative Refinement of the Approximate Posterior for Directed Belief Networks Devon Hjelm, Ruslan Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince Calhoun, Junyoung Chung

CVPRW 2016 ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation Francesco Visin, Adriana Romero, Kyunghyun Cho, Matteo Matteucci, Marco Ciccone, Kyle Kastner, Yoshua Bengio, Aaron C. Courville

NeurIPS 2015 Attention-Based Models for Speech Recognition Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, Yoshua Bengio

ICCV 2015 Describing Videos by Exploiting Temporal Structure Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle, Aaron Courville

ICLR 2015 Embedding Word Similarity with Neural Machine Translation Felix Hill, Kyunghyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio

ICML 2015 Gated Feedback Recurrent Neural Networks Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio

ICLR 2015 Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio

ICML 2015 Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, Yoshua Bengio

ICLR 2014 How to Construct Deep Recurrent Neural Networks Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio

NeurIPS 2014 Identifying and Attacking the Saddle Point Problem in High-Dimensional Non-Convex Optimization Yann N. Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio

NeurIPS 2014 Iterative Neural Autoregressive Distribution Estimator NADE-K Tapani Raiko, Yao Li, Kyunghyun Cho, Yoshua Bengio

ECML-PKDD 2014 Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks Çaglar Gülçehre, KyungHyun Cho, Razvan Pascanu, Yoshua Bengio

ECML-PKDD 2014 On the Equivalence Between Deep NADE and Generative Stochastic Networks Li Yao, Sherjil Ozair, KyungHyun Cho, Yoshua Bengio

NeurIPS 2014 On the Number of Linear Regions of Deep Neural Networks Guido F. Montufar, Razvan Pascanu, Kyunghyun Cho, Yoshua Bengio

ICLR 2013 Boltzmann Machines and Denoising Autoencoders for Image Denoising Kyunghyun Cho

ICML 2013 Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images Kyunghyun Cho

ICML 2011 Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines KyungHyun Cho, Tapani Raiko, Alexander Ilin