More from the Same Authors

• 2022 : Transform Once: Efficient Operator Learning in Frequency Domain »
  Michael Poli · Stefano Massaroli · Federico Berto · Jinkyoo Park · Tri Dao · Christopher Re · Stefano Ermon
• 2023 : The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-language Models »
  Chenwei Wu · Li Li · Stefano Ermon · Patrick Haffner · Rong Ge · Zaiwei Zhang
• 2023 : Parallel Sampling of Diffusion Models »
  Andy Shih · Suneel Belkhale · Stefano Ermon · Dorsa Sadigh · Nima Anari
• 2023 : On the Equivalence of Consistency-Type Models: Consistency Models, Consistent Diffusion Models, and Fokker-Planck Regularization »
  Chieh-Hsin Lai · Yuhta Takida · Toshimitsu Uesaka · Naoki Murata · Yuki Mitsufuji · Stefano Ermon
• 2023 : Parallel Sampling of Diffusion Models »
  Andy Shih · Suneel Belkhale · Stefano Ermon · Dorsa Sadigh · Nima Anari
• 2023 : Direct Preference Optimization: Your Language Model is Secretly a Reward Model »
  Rafael Rafailov · Archit Sharma · Eric Mitchell · Stefano Ermon · Christopher Manning · Chelsea Finn
• 2023 : Invited Talk by Stefano Ermon »
  Stefano Ermon
• 2023 Workshop: Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators »
  Felix Petersen · Marco Cuturi · Mathias Niepert · Hilde Kuehne · Michael Kagan · Willie Neiswanger · Stefano Ermon
• 2023 Oral: Hyena Hierarchy: Towards Larger Convolutional Language Models »
  Michael Poli · Stefano Massaroli · Eric Nguyen · Daniel Y Fu · Tri Dao · Stephen Baccus · Yoshua Bengio · Stefano Ermon · Christopher Re
• 2023 Poster: Geometric Latent Diffusion Models for 3D Molecule Generation »
  Minkai Xu · Alexander Powers · Ron Dror · Stefano Ermon · Jure Leskovec
• 2023 Poster: Reflected Diffusion Models »
  Aaron Lou · Stefano Ermon
• 2023 Poster: Long Horizon Temperature Scaling »
  Andy Shih · Dorsa Sadigh · Stefano Ermon
• 2023 Poster: Hyena Hierarchy: Towards Larger Convolutional Language Models »
  Michael Poli · Stefano Massaroli · Eric Nguyen · Daniel Y Fu · Tri Dao · Stephen Baccus · Yoshua Bengio · Stefano Ermon · Christopher Re
• 2023 Poster: GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration »
  Naoki Murata · Koichi Saito · Chieh-Hsin Lai · Yuhta Takida · Toshimitsu Uesaka · Yuki Mitsufuji · Stefano Ermon
• 2023 Poster: FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation »
  Chieh-Hsin Lai · Yuhta Takida · Naoki Murata · Toshimitsu Uesaka · Yuki Mitsufuji · Stefano Ermon
• 2023 Poster: Deep Latent State Space Models for Time-Series Generation »
  Linqi Zhou · Michael Poli · Winnie Xu · Stefano Massaroli · Stefano Ermon
• 2023 Oral: GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration »
  Naoki Murata · Koichi Saito · Chieh-Hsin Lai · Yuhta Takida · Toshimitsu Uesaka · Yuki Mitsufuji · Stefano Ermon
• 2023 Poster: CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations »
  Gengchen Mai · Ni Lao · Yutong He · Jiaming Song · Stefano Ermon
• 2022 : FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness »
  Tri Dao · Daniel Y Fu · Stefano Ermon · Atri Rudra · Christopher Re
• 2022 : Generative Modeling with Stochastic Differential Equations »
  Stefano Ermon
• 2022 : Neural Geometric Embedding Flows »
  Aaron Lou · Yang Song · Jiaming Song · Stefano Ermon
• 2022 Workshop: Adaptive Experimental Design and Active Learning in the Real World »
  Mojmir Mutny · Willie Neiswanger · Ilija Bogunovic · Stefano Ermon · Yisong Yue · Andreas Krause
• 2022 Poster: Imitation Learning by Estimating Expertise of Demonstrators »
  Mark Beliaev · Andy Shih · Stefano Ermon · Dorsa Sadigh · Ramtin Pedarsani
• 2022 Spotlight: Imitation Learning by Estimating Expertise of Demonstrators »
  Mark Beliaev · Andy Shih · Stefano Ermon · Dorsa Sadigh · Ramtin Pedarsani
• 2022 Poster: A General Recipe for Likelihood-free Bayesian Optimization »
  Jiaming Song · Lantao Yu · Willie Neiswanger · Stefano Ermon
• 2022 Oral: A General Recipe for Likelihood-free Bayesian Optimization »
  Jiaming Song · Lantao Yu · Willie Neiswanger · Stefano Ermon
• 2022 Poster: ButterflyFlow: Building Invertible Layers with Butterfly Matrices »
  Chenlin Meng · Linqi Zhou · Kristy Choi · Tri Dao · Stefano Ermon
• 2022 Poster: Bit Prioritization in Variational Autoencoders via Progressive Coding »
  Rui Shu · Stefano Ermon
• 2022 Poster: Modular Conformal Calibration »
  Charles Marx · Shengjia Zhao · Willie Neiswanger · Stefano Ermon
• 2022 Spotlight: Bit Prioritization in Variational Autoencoders via Progressive Coding »
  Rui Shu · Stefano Ermon
• 2022 Spotlight: Modular Conformal Calibration »
  Charles Marx · Shengjia Zhao · Willie Neiswanger · Stefano Ermon
• 2022 Spotlight: ButterflyFlow: Building Invertible Layers with Butterfly Matrices »
  Chenlin Meng · Linqi Zhou · Kristy Choi · Tri Dao · Stefano Ermon
• 2021 Poster: Temporal Predictive Coding For Model-Based Planning In Latent Space »
  Tung Nguyen · Rui Shu · Tuan Pham · Hung Bui · Stefano Ermon
• 2021 Spotlight: Temporal Predictive Coding For Model-Based Planning In Latent Space »
  Tung Nguyen · Rui Shu · Tuan Pham · Hung Bui · Stefano Ermon
• 2021 Poster: Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information »
  Willie Neiswanger · Ke Alexander Wang · Stefano Ermon
• 2021 Spotlight: Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information »
  Willie Neiswanger · Ke Alexander Wang · Stefano Ermon
• 2021 Poster: Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving »
  Yang Song · Chenlin Meng · Renjie Liao · Stefano Ermon
• 2021 Spotlight: Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving »
  Yang Song · Chenlin Meng · Renjie Liao · Stefano Ermon
• 2021 Poster: Reward Identification in Inverse Reinforcement Learning »
  Kuno Kim · Shivam Garg · Kirankumar Shiragur · Stefano Ermon
• 2021 Spotlight: Reward Identification in Inverse Reinforcement Learning »
  Kuno Kim · Shivam Garg · Kirankumar Shiragur · Stefano Ermon
• 2020 Poster: Predictive Coding for Locally-Linear Control »
  Rui Shu · Tung Nguyen · Yinlam Chow · Tuan Pham · Khoat Than · Mohammad Ghavamzadeh · Stefano Ermon · Hung Bui
• 2020 Poster: Bridging the Gap Between f-GANs and Wasserstein GANs »
  Jiaming Song · Stefano Ermon
• 2020 Poster: Individual Calibration with Randomized Forecasting »
  Shengjia Zhao · Tengyu Ma · Stefano Ermon
• 2020 Poster: Domain Adaptive Imitation Learning »
  Kuno Kim · Yihong Gu · Jiaming Song · Shengjia Zhao · Stefano Ermon
• 2020 Poster: Training Deep Energy-Based Models with f-Divergence Minimization »
  Lantao Yu · Yang Song · Jiaming Song · Stefano Ermon
• 2020 Poster: Fair Generative Modeling via Weak Supervision »
  Kristy Choi · Aditya Grover · Trisha Singh · Rui Shu · Stefano Ermon
• 2019 Poster: Calibrated Model-Based Deep Reinforcement Learning »
  Ali Malik · Volodymyr Kuleshov · Jiaming Song · Danny Nemer · Harlan Seymour · Stefano Ermon
• 2019 Poster: Graphite: Iterative Generative Modeling of Graphs »
  Aditya Grover · Aaron Zweig · Stefano Ermon
• 2019 Poster: Adaptive Antithetic Sampling for Variance Reduction »
  Hongyu Ren · Shengjia Zhao · Stefano Ermon
• 2019 Oral: Adaptive Antithetic Sampling for Variance Reduction »
  Hongyu Ren · Shengjia Zhao · Stefano Ermon
• 2019 Oral: Graphite: Iterative Generative Modeling of Graphs »
  Aditya Grover · Aaron Zweig · Stefano Ermon
• 2019 Oral: Calibrated Model-Based Deep Reinforcement Learning »
  Ali Malik · Volodymyr Kuleshov · Jiaming Song · Danny Nemer · Harlan Seymour · Stefano Ermon
• 2019 Poster: Multi-Agent Adversarial Inverse Reinforcement Learning »
  Lantao Yu · Jiaming Song · Stefano Ermon
• 2019 Poster: Neural Joint Source-Channel Coding »
  Kristy Choi · Kedar Tatwawadi · Aditya Grover · Tsachy Weissman · Stefano Ermon
• 2019 Oral: Neural Joint Source-Channel Coding »
  Kristy Choi · Kedar Tatwawadi · Aditya Grover · Tsachy Weissman · Stefano Ermon
• 2019 Oral: Multi-Agent Adversarial Inverse Reinforcement Learning »
  Lantao Yu · Jiaming Song · Stefano Ermon
• 2018 Poster: Modeling Sparse Deviations for Compressed Sensing using Generative Models »
  Manik Dhar · Aditya Grover · Stefano Ermon
• 2018 Oral: Modeling Sparse Deviations for Compressed Sensing using Generative Models »
  Manik Dhar · Aditya Grover · Stefano Ermon
• 2018 Poster: Accelerating Natural Gradient with Higher-Order Invariance »
  Yang Song · Jiaming Song · Stefano Ermon
• 2018 Poster: Accurate Uncertainties for Deep Learning Using Calibrated Regression »
  Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
• 2018 Oral: Accelerating Natural Gradient with Higher-Order Invariance »
  Yang Song · Jiaming Song · Stefano Ermon
• 2018 Oral: Accurate Uncertainties for Deep Learning Using Calibrated Regression »
  Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
• 2017 Poster: Learning Hierarchical Features from Deep Generative Models »
  Shengjia Zhao · Jiaming Song · Stefano Ermon
• 2017 Talk: Learning Hierarchical Features from Deep Generative Models »
  Shengjia Zhao · Jiaming Song · Stefano Ermon