Timezone: »
Stefano Emron - Generative Modeling via Denoising
Stefano Ermon
Author Information
Stefano Ermon (Stanford)
More from the Same Authors
-
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: 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 : 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 : LMPriors: Pre-Trained Language Models as Task-Specific Priors »
Kristy Choi · Chris Cundy · Sanjari Srivastava · Stefano Ermon -
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 -
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 -
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: 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: 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: 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: 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: Improving Self-Supervised Learning by Characterizing Idealized Representations »
Yann Dubois · Stefano Ermon · Tatsunori Hashimoto · 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 : Cundy, Grover, Ermon - BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery »
Chris Cundy · Aditya Grover · Stefano Ermon -
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: 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 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: 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: 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 : 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: 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: 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 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: 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 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 -
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 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 -
2016 Poster: Solving Marginal MAP Problems with NP Oracles and Parity Constraints »
Yexiang Xue · zhiyuan li · Stefano Ermon · Carla Gomes · Bart Selman -
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 -
2013 Poster: Embed and Project: Discrete Sampling with Universal Hashing »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
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