Timezone: »
Despite the empirical successes of self-supervised learning (SSL) methods, it is unclear what characteristics of their representations lead to high downstream accuracies. In this work, we characterize properties that SSL representations should ideally satisfy. Specifically, we prove necessary and sufficient conditions such that for any task invariant to given data augmentations, probes (e.g., linear or MLP) trained on that representation attain perfect accuracy. These requirements lead to a unifying conceptual framework for improving existing SSL methods and deriving new ones. For contrastive learning, our framework prescribes simple but significant improvements to previous methods such as using asymmetric projection heads. For non-contrastive learning, we use our framework to derive a simple and novel objective. Our resulting SSL algorithms outperform baselines on standard benchmarks, including SwAV+multicrops on linear probing of ImageNet.
Author Information
Yann Dubois (Stanford University)
Stefano Ermon (Stanford)
Tatsunori Hashimoto (Stanford)
Percy Liang (Stanford University)

Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His research spans machine learning and natural language processing, with the goal of developing trustworthy agents that can communicate effectively with people and improve over time through interaction. Specific topics include question answering, dialogue, program induction, interactive learning, and reliable machine learning. His awards include the IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).
More from the Same Authors
-
2020 : Invited Talk 8 Presentation - Percy Liang - Semantic Parsing for Natural Language Interfaces »
Percy Liang -
2020 : Paper 46: Disagreement-Regularized Imitation of Complex Multi-Agent Interactions »
Jiaming Song · Stefano Ermon -
2021 Spotlight: IQ-Learn: Inverse soft-Q Learning for Imitation »
Divyansh Garg · Shuvam Chakraborty · Chris Cundy · Jiaming Song · Stefano Ermon -
2021 Spotlight: Lossy Compression for Lossless Prediction »
Yann Dubois · Benjamin Bloem-Reddy · Karen Ullrich · Chris Maddison -
2021 Spotlight: Maximum Likelihood Training of Score-Based Diffusion Models »
Yang Song · Conor Durkan · Iain Murray · Stefano Ermon -
2021 : SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning »
Christopher Yeh · Chenlin Meng · Sherrie Wang · Anne Driscoll · Erik Rozi · Patrick Liu · Jihyeon Lee · Marshall Burke · David Lobell · Stefano Ermon -
2021 : Optimal Representations for Covariate Shifts »
Yann Dubois · Yangjun Ruan · Chris Maddison -
2021 : Scalable Variational Approaches for Bayesian Causal Discovery »
Chris Cundy · Aditya Grover · Stefano Ermon -
2021 : Likelihood-free Density Ratio Acquisition Functions are not Equivalent to Expected Improvements »
Jiaming Song · Stefano Ermon -
2022 : A Closer Look at the Calibration of Differential Private Learners »
Hanlin Zhang · Xuechen (Chen) Li · Prithviraj Sen · Salim Roukos · Tatsunori Hashimoto -
2022 : LMPriors: Pre-Trained Language Models as Task-Specific Priors »
Kristy Choi · Chris Cundy · Sanjari Srivastava · Stefano Ermon -
2022 : Out-of-Distribution Robustness via Targeted Augmentations »
Irena Gao · Shiori Sagawa · Pang Wei Koh · Tatsunori Hashimoto · Percy Liang -
2022 : Surgical Fine-Tuning Improves Adaptation to Distribution Shifts »
Yoonho Lee · Annie Chen · Fahim Tajwar · Ananya Kumar · Huaxiu Yao · Percy Liang · Chelsea Finn -
2022 : Data Feedback Loops: Model-driven Amplification of Dataset Biases »
Rohan Taori · Tatsunori Hashimoto -
2022 : Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification »
Niladri S. Chatterji · Saminul Haque · Tatsunori Hashimoto -
2022 : Relaxing the Kolmogorov Structure Function for Realistic Computational Constraints »
Yoonho Lee · Chelsea Finn · Stefano Ermon -
2022 : Regularizing Score-based Models with Score Fokker-Planck Equations »
Chieh-Hsin Lai · Yuhta Takida · Naoki Murata · Toshimitsu Uesaka · Yuki Mitsufuji · Stefano Ermon -
2022 : On Distillation of Guided Diffusion Models »
Chenlin Meng · Ruiqi Gao · Diederik Kingma · Stefano Ermon · Jonathan Ho · Tim Salimans -
2022 : JPEG Artifact Correction using Denoising Diffusion Restoration Models »
Bahjat Kawar · Jiaming Song · Stefano Ermon · Michael Elad -
2022 : But Are You Sure? Quantifying Uncertainty in Model Explanations »
Charles Marx · Youngsuk Park · Hilaf Hasson · Yuyang (Bernie) Wang · Stefano Ermon · Chaitanya Baru -
2022 : Surgical Fine-Tuning Improves Adaptation to Distribution Shifts »
Yoonho Lee · Annie Chen · Fahim Tajwar · Ananya Kumar · Huaxiu Yao · Percy Liang · Chelsea Finn -
2023 Poster: UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild »
Can Qin · Shu Zhang · Ning Yu · Yihao Feng · Xinyi Yang · Yingbo Zhou · Huan Wang · Juan Carlos Niebles · Caiming Xiong · Silvio Savarese · Stefano Ermon · Yun Fu · Ran Xu -
2023 Poster: HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution »
Eric Nguyen · Michael Poli · Marjan Faizi · Armin Thomas · Michael Wornow · Callum Birch-Sykes · Stefano Massaroli · Aman Patel · Clayton Rabideau · Yoshua Bengio · Stefano Ermon · Christopher Ré · Stephen Baccus -
2023 Poster: Data Selection for Language Models via Importance Resampling »
Sang Michael Xie · Shibani Santurkar · Tengyu Ma · Percy Liang -
2023 Poster: PRODIGY: Enabling In-context Learning Over Graphs »
Qian Huang · Hongyu Ren · Peng Chen · Gregor Kržmanc · Daniel Zeng · Percy Liang · Jure Leskovec -
2023 Poster: DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining »
Sang Michael Xie · Hieu Pham · Xuanyi Dong · Nan Du · Hanxiao Liu · Yifeng Lu · Percy Liang · Quoc V Le · Tengyu Ma · Adams Wei Yu -
2023 Poster: Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation »
Yuxuan Song · Jingjing Gong · Minkai Xu · Ziyao Cao · Yanyan Lan · Stefano Ermon · Hao Zhou · Wei-Ying Ma -
2023 Poster: Likelihood-Based Diffusion Language Models »
Ishaan Gulrajani · Tatsunori Hashimoto -
2023 Poster: Parallel Sampling of Diffusion Models »
Andy Shih · Suneel Belkhale · Stefano Ermon · Dorsa Sadigh · Nima Anari -
2023 Poster: MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks »
Allen Nie · Yuhui Zhang · Atharva Shailesh Amdekar · Chris Piech · Tatsunori Hashimoto · Tobias Gerstenberg -
2023 Poster: Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs »
Deepak Narayanan · Keshav Santhanam · Peter Henderson · Rishi Bommasani · Tony Lee · Percy Liang -
2023 Poster: Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions »
Stefano Massaroli · Michael Poli · Dan Fu · Hermann Kumbong · David Romero · Rom Parnichkun · Aman Timalsina · Quinn McIntyre · Beidi Chen · Atri Rudra · Ce Zhang · Christopher Ré · Stefano Ermon · Yoshua Bengio -
2023 Poster: Lexinvariant Language Models »
Qian Huang · Eric Zelikman · Sarah Chen · Yuhuai Wu · Gregory Valiant · Percy Liang -
2023 Poster: Calibration by Distribution Matching: Trainable Kernel Calibration Metrics »
Charles Marx · Sofian Zalouk · Stefano Ermon -
2023 Poster: Direct Preference Optimization: Your Language Model is Secretly a Reward Model »
Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn -
2023 Poster: Scaling Riemannian Diffusion Models »
Aaron Lou · Minkai Xu · Adam Farris · Stefano Ermon -
2023 Poster: Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes »
Connor Toups · Rishi Bommasani · Kathleen Creel · Sarah Bana · Dan Jurafsky · Percy Liang -
2023 Poster: AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback »
Yann Dubois · Xuechen Li · Rohan Taori · Tianyi Zhang · Ishaan Gulrajani · Jimmy Ba · Carlos Guestrin · Percy Liang · Tatsunori Hashimoto -
2023 Poster: Holistic Evaluation of Text-to-Image Models »
Tony Lee · Michihiro Yasunaga · Chenlin Meng · Yifan Mai · Joon Sung Park · Agrim Gupta · Yunzhi Zhang · Deepak Narayanan · Hannah Teufel · Marco Bellagente · Minguk Kang · Taesung Park · Jure Leskovec · Jun-Yan Zhu · Fei-Fei Li · Jiajun Wu · Stefano Ermon · Percy Liang -
2023 Poster: GEO-Bench: Toward Foundation Models for Earth Monitoring »
Alexandre Lacoste · Nils Lehmann · Pau Rodriguez · Evan Sherwin · Hannah Kerner · Björn Lütjens · Jeremy Irvin · David Dao · Hamed Alemohammad · Alexandre Drouin · Mehmet Gunturkun · Gabriel Huang · David Vazquez · Dava Newman · Yoshua Bengio · Stefano Ermon · Xiaoxiang Zhu -
2023 Oral: Direct Preference Optimization: Your Language Model is Secretly a Reward Model »
Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn -
2023 Workshop: Adaptive Experimental Design and Active Learning in the Real World »
Willie Neiswanger · Mojmir Mutny · Ilija Bogunovic · Ava Soleimany · Zi Wang · Stefano Ermon · Andreas Krause -
2023 Workshop: Generative AI and Biology (GenBio@NeurIPS2023) »
Minkai Xu · Regina Barzilay · Jure Leskovec · Wenxian Shi · Menghua Wu · Zhenqiao Song · Lei Li · Fan Yang · Stefano Ermon -
2023 Workshop: Workshop on Distribution Shifts: New Frontiers with Foundation Models »
Rebecca Roelofs · Fanny Yang · Hongseok Namkoong · Masashi Sugiyama · Jacob Eisenstein · Pang Wei Koh · Shiori Sagawa · Tatsunori Hashimoto · Yoonho Lee -
2022 : Data Feedback Loops: Model-driven Amplification of Dataset Biases »
Rohan Taori · Tatsunori Hashimoto -
2022 : Fine-Tuning without Distortion: Improving Robustness to Distribution Shifts »
Percy Liang · Ananya Kumar -
2022 Workshop: MATH-AI: Toward Human-Level Mathematical Reasoning »
Pan Lu · Swaroop Mishra · Sean Welleck · Yuhuai Wu · Hannaneh Hajishirzi · Percy Liang -
2022 Poster: What Can Transformers Learn In-Context? A Case Study of Simple Function Classes »
Shivam Garg · Dimitris Tsipras · Percy Liang · Gregory Valiant -
2022 Poster: Insights into Pre-training via Simpler Synthetic Tasks »
Yuhuai Wu · Felix Li · Percy Liang -
2022 Poster: Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models »
Muyang Li · Ji Lin · Chenlin Meng · Stefano Ermon · Song Han · Jun-Yan Zhu -
2022 Poster: When Does Differentially Private Learning Not Suffer in High Dimensions? »
Xuechen Li · Daogao Liu · Tatsunori Hashimoto · Huseyin A. Inan · Janardhan Kulkarni · Yin-Tat Lee · Abhradeep Guha Thakurta -
2022 Poster: Concrete Score Matching: Generalized Score Matching for Discrete Data »
Chenlin Meng · Kristy Choi · Jiaming Song · Stefano Ermon -
2022 Poster: LISA: Learning Interpretable Skill Abstractions from Language »
Divyansh Garg · Skanda Vaidyanath · Kuno Kim · Jiaming Song · Stefano Ermon -
2022 Poster: Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits »
Tong Mu · Yash Chandak · Tatsunori Hashimoto · Emma Brunskill -
2022 Poster: Training and Inference on Any-Order Autoregressive Models the Right Way »
Andy Shih · Dorsa Sadigh · Stefano Ermon -
2022 Poster: SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery »
Yezhen Cong · Samar Khanna · Chenlin Meng · Patrick Liu · Erik Rozi · Yutong He · Marshall Burke · David Lobell · Stefano Ermon -
2022 Poster: Deep Bidirectional Language-Knowledge Graph Pretraining »
Michihiro Yasunaga · Antoine Bosselut · Hongyu Ren · Xikun Zhang · Christopher D Manning · Percy Liang · Jure Leskovec -
2022 Poster: FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness »
Tri Dao · Dan Fu · Stefano Ermon · Atri Rudra · Christopher Ré -
2022 Poster: Denoising Diffusion Restoration Models »
Bahjat Kawar · Michael Elad · Stefano Ermon · Jiaming Song -
2022 Poster: Generalizing Bayesian Optimization with Decision-theoretic Entropies »
Willie Neiswanger · Lantao Yu · Shengjia Zhao · Chenlin Meng · Stefano Ermon -
2022 Poster: Decentralized Training of Foundation Models in Heterogeneous Environments »
Binhang Yuan · Yongjun He · Jared Davis · Tianyi Zhang · Tri Dao · Beidi Chen · Percy Liang · Christopher Ré · Ce Zhang -
2022 Poster: Transform Once: Efficient Operator Learning in Frequency Domain »
Michael Poli · Stefano Massaroli · Federico Berto · Jinkyoo Park · Tri Dao · Christopher Ré · Stefano Ermon -
2022 Poster: Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations »
Michael Poli · Winnie Xu · Stefano Massaroli · Chenlin Meng · Kuno Kim · Stefano Ermon -
2022 Poster: Diffusion-LM Improves Controllable Text Generation »
Xiang Li · John Thickstun · Ishaan Gulrajani · Percy Liang · Tatsunori Hashimoto -
2022 Poster: Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? »
Rishi Bommasani · Kathleen A. Creel · Ananya Kumar · Dan Jurafsky · Percy Liang -
2022 Poster: Exploration via Planning for Information about the Optimal Trajectory »
Viraj Mehta · Ian Char · Joseph Abbate · Rory Conlin · Mark Boyer · Stefano Ermon · Jeff Schneider · Willie Neiswanger -
2021 : TorchDyn: Implicit Models and Neural Numerical Methods in PyTorch »
Michael Poli · Stefano Massaroli · Atsushi Yamashita · Hajime Asama · Jinkyoo Park · Stefano Ermon -
2021 : Panel: Future directions for tackling distribution shifts »
Tatsunori Hashimoto · Jamie Morgenstern · Judy Hoffman · Andrew Beck -
2021 : Cundy, Grover, Ermon - BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery »
Chris Cundy · Aditya Grover · Stefano Ermon -
2021 Workshop: Distribution shifts: connecting methods and applications (DistShift) »
Shiori Sagawa · Pang Wei Koh · Fanny Yang · Hongseok Namkoong · Jiashi Feng · Kate Saenko · Percy Liang · Sarah Bird · Sergey Levine -
2021 Workshop: CtrlGen: Controllable Generative Modeling in Language and Vision »
Steven Y. Feng · Dor Arad Hudson · Tatsunori Hashimoto · DONGYEOP Kang · Varun Prashant Gangal · Anusha Balakrishnan · Joel Tetreault -
2021 Poster: HyperSPNs: Compact and Expressive Probabilistic Circuits »
Andy Shih · Dorsa Sadigh · Stefano Ermon -
2021 Poster: Imitation with Neural Density Models »
Kuno Kim · Akshat Jindal · Yang Song · Jiaming Song · Yanan Sui · Stefano Ermon -
2021 Poster: Reliable Decisions with Threshold Calibration »
Roshni Sahoo · Shengjia Zhao · Alyssa Chen · Stefano Ermon -
2021 Poster: D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation »
Abhishek Sinha · Jiaming Song · Chenlin Meng · Stefano Ermon -
2021 Poster: Improving Compositionality of Neural Networks by Decoding Representations to Inputs »
Mike Wu · Noah Goodman · Stefano Ermon -
2021 Poster: Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis »
Yutong He · Dingjie Wang · Nicholas Lai · William Zhang · Chenlin Meng · Marshall Burke · David Lobell · Stefano Ermon -
2021 Poster: Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration »
Shengjia Zhao · Michael Kim · Roshni Sahoo · Tengyu Ma · Stefano Ermon -
2021 Poster: Estimating High Order Gradients of the Data Distribution by Denoising »
Chenlin Meng · Yang Song · Wenzhe Li · Stefano Ermon -
2021 Poster: Maximum Likelihood Training of Score-Based Diffusion Models »
Yang Song · Conor Durkan · Iain Murray · Stefano Ermon -
2021 Poster: Pseudo-Spherical Contrastive Divergence »
Lantao Yu · Jiaming Song · Yang Song · Stefano Ermon -
2021 Poster: IQ-Learn: Inverse soft-Q Learning for Imitation »
Divyansh Garg · Shuvam Chakraborty · Chris Cundy · Jiaming Song · Stefano Ermon -
2021 Poster: Lossy Compression for Lossless Prediction »
Yann Dubois · Benjamin Bloem-Reddy · Karen Ullrich · Chris Maddison -
2021 Poster: CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation »
Yusuke Tashiro · Jiaming Song · Yang Song · Stefano Ermon -
2021 Poster: PiRank: Scalable Learning To Rank via Differentiable Sorting »
Robin Swezey · Aditya Grover · Bruno Charron · Stefano Ermon -
2021 Poster: BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery »
Chris Cundy · Aditya Grover · Stefano Ermon -
2020 : Invited Talk 8 Q/A - Percy Liang »
Percy Liang -
2020 : Stefano Emron - Generative Modeling via Denoising »
Stefano Ermon -
2020 Poster: Improved Techniques for Training Score-Based Generative Models »
Yang Song · Stefano Ermon -
2020 Poster: Probabilistic Circuits for Variational Inference in Discrete Graphical Models »
Andy Shih · Stefano Ermon -
2020 Poster: Efficient Learning of Generative Models via Finite-Difference Score Matching »
Tianyu Pang · Kun Xu · Chongxuan LI · Yang Song · Stefano Ermon · Jun Zhu -
2020 Poster: Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes »
Andrew Foong · Wessel Bruinsma · Jonathan Gordon · Yann Dubois · James Requeima · Richard Turner -
2020 Poster: Belief Propagation Neural Networks »
Jonathan Kuck · Shuvam Chakraborty · Hao Tang · Rachel Luo · Jiaming Song · Ashish Sabharwal · Stefano Ermon -
2020 Poster: HiPPO: Recurrent Memory with Optimal Polynomial Projections »
Albert Gu · Tri Dao · Stefano Ermon · Atri Rudra · Christopher Ré -
2020 Spotlight: HiPPO: Recurrent Memory with Optimal Polynomial Projections »
Albert Gu · Tri Dao · Stefano Ermon · Atri Rudra · Christopher Ré -
2020 Poster: Autoregressive Score Matching »
Chenlin Meng · Lantao Yu · Yang Song · Jiaming Song · Stefano Ermon -
2020 Poster: Learning Optimal Representations with the Decodable Information Bottleneck »
Yann Dubois · Douwe Kiela · David Schwab · Ramakrishna Vedantam -
2020 Poster: Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming »
Sumanth Dathathri · Krishnamurthy Dvijotham · Alexey Kurakin · Aditi Raghunathan · Jonathan Uesato · Rudy Bunel · Shreya Shankar · Jacob Steinhardt · Ian Goodfellow · Percy Liang · Pushmeet Kohli -
2020 Spotlight: Learning Optimal Representations with the Decodable Information Bottleneck »
Yann Dubois · Douwe Kiela · David Schwab · Ramakrishna Vedantam -
2020 Poster: Diversity can be Transferred: Output Diversification for White- and Black-box Attacks »
Yusuke Tashiro · Yang Song · Stefano Ermon -
2020 Poster: MOPO: Model-based Offline Policy Optimization »
Tianhe Yu · Garrett Thomas · Lantao Yu · Stefano Ermon · James Zou · Sergey Levine · Chelsea Finn · Tengyu Ma -
2020 Poster: Multi-label Contrastive Predictive Coding »
Jiaming Song · Stefano Ermon -
2020 Oral: Multi-label Contrastive Predictive Coding »
Jiaming Song · Stefano Ermon -
2019 : Extended Poster Session »
Travis LaCroix · Marie Ossenkopf · Mina Lee · Nicole Fitzgerald · Daniela Mihai · Jonathon Hare · Ali Zaidi · Alexander Cowen-Rivers · Alana Marzoev · Eugene Kharitonov · Luyao Yuan · Tomasz Korbak · Paul Pu Liang · Yi Ren · Roberto Dessì · Peter Potash · Shangmin Guo · Tatsunori Hashimoto · Percy Liang · Julian Zubek · Zipeng Fu · Song-Chun Zhu · Adam Lerer -
2019 : Poster Session »
Ethan Harris · Tom White · Oh Hyeon Choung · Takashi Shinozaki · Dipan Pal · Katherine L. Hermann · Judy Borowski · Camilo Fosco · Chaz Firestone · Vijay Veerabadran · Benjamin Lahner · Chaitanya Ryali · Fenil Doshi · Pulkit Singh · Sharon Zhou · Michel Besserve · Michael Chang · Anelise Newman · Mahesan Niranjan · Jonathon Hare · Daniela Mihai · Marios Savvides · Simon Kornblith · Christina M Funke · Aude Oliva · Virginia de Sa · Dmitry Krotov · Colin Conwell · George Alvarez · Alex Kolchinski · Shengjia Zhao · Mitchell Gordon · Michael Bernstein · Stefano Ermon · Arash Mehrjou · Bernhard Schölkopf · John Co-Reyes · Michael Janner · Jiajun Wu · Josh Tenenbaum · Sergey Levine · Yalda Mohsenzadeh · Zhenglong Zhou -
2019 Workshop: Information Theory and Machine Learning »
Shengjia Zhao · Jiaming Song · Yanjun Han · Kristy Choi · Pratyusha Kalluri · Ben Poole · Alex Dimakis · Jiantao Jiao · Tsachy Weissman · Stefano Ermon -
2019 Poster: SPoC: Search-based Pseudocode to Code »
Sumith Kulal · Panupong Pasupat · Kartik Chandra · Mina Lee · Oded Padon · Alex Aiken · Percy Liang -
2019 Poster: On the Accuracy of Influence Functions for Measuring Group Effects »
Pang Wei Koh · Kai-Siang Ang · Hubert Teo · Percy Liang -
2019 Poster: Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations. »
Sawyer Birnbaum · Volodymyr Kuleshov · Zayd Enam · Pang Wei Koh · Stefano Ermon -
2019 Poster: MintNet: Building Invertible Neural Networks with Masked Convolutions »
Yang Song · Chenlin Meng · Stefano Ermon -
2019 Poster: Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting »
Aditya Grover · Jiaming Song · Ashish Kapoor · Kenneth Tran · Alekh Agarwal · Eric Horvitz · Stefano Ermon -
2019 Poster: Meta-Inverse Reinforcement Learning with Probabilistic Context Variables »
Lantao Yu · Tianhe Yu · Chelsea Finn · Stefano Ermon -
2019 Poster: Approximating the Permanent by Sampling from Adaptive Partitions »
Jonathan Kuck · Tri Dao · Hamid Rezatofighi · Ashish Sabharwal · Stefano Ermon -
2019 Poster: Verified Uncertainty Calibration »
Ananya Kumar · Percy Liang · Tengyu Ma -
2019 Spotlight: Verified Uncertainty Calibration »
Ananya Kumar · Percy Liang · Tengyu Ma -
2019 Poster: Generative Modeling by Estimating Gradients of the Data Distribution »
Yang Song · Stefano Ermon -
2019 Oral: Generative Modeling by Estimating Gradients of the Data Distribution »
Yang Song · Stefano Ermon -
2018 : Natural Language Supervision »
Percy Liang -
2018 Workshop: Relational Representation Learning »
Aditya Grover · Paroma Varma · Frederic Sala · Christopher Ré · Jennifer Neville · Stefano Ermon · Steven Holtzen -
2018 : Stefano Ermon (Stanford University): Weakly Supervised Spatio-temporal Regression »
Stefano Ermon -
2018 Poster: Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss »
Stephen Mussmann · Percy Liang -
2018 Poster: Streamlining Variational Inference for Constraint Satisfaction Problems »
Aditya Grover · Tudor Achim · Stefano Ermon -
2018 Poster: Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance »
Neal Jean · Sang Michael Xie · Stefano Ermon -
2018 Poster: Multi-Agent Generative Adversarial Imitation Learning »
Jiaming Song · Hongyu Ren · Dorsa Sadigh · Stefano Ermon -
2018 Poster: Constructing Unrestricted Adversarial Examples with Generative Models »
Yang Song · Rui Shu · Nate Kushman · Stefano Ermon -
2018 Poster: Bias and Generalization in Deep Generative Models: An Empirical Study »
Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Noah Goodman · Stefano Ermon -
2018 Poster: Semidefinite relaxations for certifying robustness to adversarial examples »
Aditi Raghunathan · Jacob Steinhardt · Percy Liang -
2018 Spotlight: Bias and Generalization in Deep Generative Models: An Empirical Study »
Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Noah Goodman · Stefano Ermon -
2018 Poster: Amortized Inference Regularization »
Rui Shu · Hung Bui · Shengjia Zhao · Mykel J Kochenderfer · Stefano Ermon -
2018 Poster: A Retrieve-and-Edit Framework for Predicting Structured Outputs »
Tatsunori Hashimoto · Kelvin Guu · Yonatan Oren · Percy Liang -
2018 Oral: A Retrieve-and-Edit Framework for Predicting Structured Outputs »
Tatsunori Hashimoto · Kelvin Guu · Yonatan Oren · Percy Liang -
2017 : Generative Adversarial Imitation Learning, Stefano Ermon, Stanford »
Stefano Ermon -
2017 : Stefano Ermon (Stanford): Measuring Progress Towards Sustainable Development Goals with Machine Learning »
Stefano Ermon -
2017 : (Invited Talk) Percy Liang: Learning with Adversaries and Collaborators »
Percy Liang -
2017 Workshop: Machine Learning and Computer Security »
Jacob Steinhardt · Nicolas Papernot · Bo Li · Chang Liu · Percy Liang · Dawn Song -
2017 Demonstration: Babble Labble: Learning from Natural Language Explanations »
Braden Hancock · Paroma Varma · Percy Liang · Christopher Ré · Stephanie Wang -
2017 Poster: Learning Overcomplete HMMs »
Vatsal Sharan · Sham Kakade · Percy Liang · Gregory Valiant -
2017 Poster: Certified Defenses for Data Poisoning Attacks »
Jacob Steinhardt · Pang Wei Koh · Percy Liang -
2017 Poster: A-NICE-MC: Adversarial Training for MCMC »
Jiaming Song · Shengjia Zhao · Stefano Ermon -
2017 Poster: InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations »
Yunzhu Li · Jiaming Song · Stefano Ermon -
2017 Poster: Neural Variational Inference and Learning in Undirected Graphical Models »
Volodymyr Kuleshov · Stefano Ermon -
2017 Poster: Unsupervised Transformation Learning via Convex Relaxations »
Tatsunori Hashimoto · Percy Liang · John Duchi -
2016 Workshop: Deep Learning for Action and Interaction »
Chelsea Finn · Raia Hadsell · David Held · Sergey Levine · Percy Liang -
2016 Workshop: Nonconvex Optimization for Machine Learning: Theory and Practice »
Hossein Mobahi · Anima Anandkumar · Percy Liang · Stefanie Jegelka · Anna Choromanska -
2016 Workshop: Reliable Machine Learning in the Wild »
Dylan Hadfield-Menell · Adrian Weller · David Duvenaud · Jacob Steinhardt · Percy Liang -
2016 Poster: Solving Marginal MAP Problems with NP Oracles and Parity Constraints »
Yexiang Xue · zhiyuan li · Stefano Ermon · Carla Gomes · Bart Selman -
2016 Poster: Unsupervised Risk Estimation Using Only Conditional Independence Structure »
Jacob Steinhardt · Percy Liang -
2016 Poster: Generative Adversarial Imitation Learning »
Jonathan Ho · Stefano Ermon -
2016 Poster: Variational Bayes on Monte Carlo Steroids »
Aditya Grover · Stefano Ermon -
2016 Poster: Adaptive Concentration Inequalities for Sequential Decision Problems »
Shengjia Zhao · Enze Zhou · Ashish Sabharwal · Stefano Ermon -
2015 : Sharing the "How" (and not the "What") »
Percy Liang -
2015 Workshop: Non-convex Optimization for Machine Learning: Theory and Practice »
Anima Anandkumar · Niranjan Uma Naresh · Kamalika Chaudhuri · Percy Liang · Sewoong Oh -
2015 Demonstration: CodaLab Worksheets for Reproducible, Executable Papers »
Percy Liang · Evelyne Viegas -
2015 Poster: On-the-Job Learning with Bayesian Decision Theory »
Keenon Werling · Arun Tejasvi Chaganty · Percy Liang · Christopher Manning -
2015 Spotlight: On-the-Job Learning with Bayesian Decision Theory »
Keenon Werling · Arun Tejasvi Chaganty · Percy Liang · Christopher Manning -
2015 Poster: Estimating Mixture Models via Mixtures of Polynomials »
Sida Wang · Arun Tejasvi Chaganty · Percy Liang -
2015 Poster: Learning with Relaxed Supervision »
Jacob Steinhardt · Percy Liang -
2015 Poster: Calibrated Structured Prediction »
Volodymyr Kuleshov · Percy Liang -
2014 Workshop: Challenges in Machine Learning workshop (CiML 2014) »
Isabelle Guyon · Evelyne Viegas · Percy Liang · Olga Russakovsky · Rinat Sergeev · Gábor Melis · Michele Sebag · Gustavo Stolovitzky · Jaume Bacardit · Michael S Kim · Ben Hamner -
2014 Poster: Altitude Training: Strong Bounds for Single-Layer Dropout »
Stefan Wager · William S Fithian · Sida Wang · Percy Liang -
2014 Poster: Simple MAP Inference via Low-Rank Relaxations »
Roy Frostig · Sida Wang · Percy Liang · Christopher D Manning -
2013 Poster: Dropout Training as Adaptive Regularization »
Stefan Wager · Sida Wang · Percy Liang -
2013 Spotlight: Dropout Training as Adaptive Regularization »
Stefan Wager · Sida Wang · Percy Liang -
2013 Poster: Embed and Project: Discrete Sampling with Universal Hashing »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2012 Poster: Identifiability and Unmixing of Latent Parse Trees »
Percy Liang · Sham M Kakade · Daniel Hsu -
2012 Poster: Density Propagation and Improved Bounds on the Partition Function »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Poster: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Spotlight: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2009 Workshop: The Generative and Discriminative Learning Interface »
Simon Lacoste-Julien · Percy Liang · Guillaume Bouchard -
2009 Poster: Asymptotically Optimal Regularization in Smooth Parametric Models »
Percy Liang · Francis Bach · Guillaume Bouchard · Michael Jordan -
2008 Workshop: Speech and Language: Unsupervised Latent-Variable Models »
Slav Petrov · Aria Haghighi · Percy Liang · Dan Klein -
2007 Poster: Agreement-Based Learning »
Percy Liang · Dan Klein · Michael Jordan -
2007 Spotlight: Agreement-Based Learning »
Percy Liang · Dan Klein · Michael Jordan -
2007 Poster: A Probabilistic Approach to Language Change »
Alexandre Bouchard-Côté · Percy Liang · Tom Griffiths · Dan Klein