Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDStefano Ermon
Person information
- affiliation: Stanford University
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j9]Gengchen Mai
, Chiyu Jiang, Weiwei Sun, Rui Zhu, Yao Xuan, Ling Cai, Krzysztof Janowicz, Stefano Ermon, Ni Lao:
Towards general-purpose representation learning of polygonal geometries. GeoInformatica 27(2): 289-340 (2023)- [j8]Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14465-14480 (2023) - [j7]Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H.-S. Philip Wong, Armin Alaghi:
Neural Network Compression for Noisy Storage Devices. ACM Trans. Embed. Comput. Syst. 22(3): 58:1-58:29 (2023) - [c217]Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon:
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching. AAAI 2023: 11016-11024 - [c216]Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan:
But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI. AISTATS 2023: 7375-7391 - [c215]Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz:
Ideal Abstractions for Decision-Focused Learning. AISTATS 2023: 10223-10234 - [c214]Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans:
On Distillation of Guided Diffusion Models. CVPR 2023: 14297-14306 - [c213]Benedikt Boecking, Nicholas Roberts, Willie Neiswanger, Stefano Ermon, Frederic Sala, Artur Dubrawski:
Generative Modeling Helps Weak Supervision (and Vice Versa). ICLR 2023 - [c212]Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon:
Extreme Q-Learning: MaxEnt RL without Entropy. ICLR 2023 - [c211]Kuno Kim, Stefano Ermon:
Understanding and Adopting Rational Behavior by Bellman Score Estimation. ICLR 2023 - [c210]Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon:
Dual Diffusion Implicit Bridges for Image-to-Image Translation. ICLR 2023 - [c209]Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon:
FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation. ICML 2023: 18365-18398 - [c208]Aaron Lou, Stefano Ermon:
Reflected Diffusion Models. ICML 2023: 22675-22701 - [c207]Gengchen Mai, Ni Lao, Yutong He, Jiaming Song, Stefano Ermon:
CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations. ICML 2023: 23498-23515 - [c206]Naoki Murata, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon:
GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration. ICML 2023: 25501-25522 - [c205]Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré:
Hyena Hierarchy: Towards Larger Convolutional Language Models. ICML 2023: 28043-28078 - [c204]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Long Horizon Temperature Scaling. ICML 2023: 31422-31434 - [c203]Minkai Xu, Alexander S. Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec:
Geometric Latent Diffusion Models for 3D Molecule Generation. ICML 2023: 38592-38610 - [c202]Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon:
Deep Latent State Space Models for Time-Series Generation. ICML 2023: 42625-42643 - [c201]Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon:
Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834 - [c200]Chenlin Meng, Jiaming Song, Shuang Li, Jun-Yan Zhu, Stefano Ermon, Tsung-Yi Lin, Chen-Hsuan Lin, Karsten Kreis:
SIGGRAPH 2023 Course on Diffusion Models. SIGGRAPH Courses 2023: 7:1-7:113 - [i221]Enci Liu, Chenlin Meng, Matthew Kolodner, Eun Jee Sung, Sihang Chen, Marshall Burke, David B. Lobell, Stefano Ermon:
Building Coverage Estimation with Low-resolution Remote Sensing Imagery. CoRR abs/2301.01449 (2023) - [i220]Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon:
Extreme Q-Learning: MaxEnt RL without Entropy. CoRR abs/2301.02328 (2023) - [i219]Naoki Murata, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon:
GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration. CoRR abs/2301.12686 (2023) - [i218]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Long Horizon Temperature Scaling. CoRR abs/2302.03686 (2023) - [i217]Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré:
Hyena Hierarchy: Towards Larger Convolutional Language Models. CoRR abs/2302.10866 (2023) - [i216]Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon:
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching. CoRR abs/2303.02569 (2023) - [i215]Shu Zhang, Xinyi Yang, Yihao Feng, Can Qin, Chia-Chih Chen, Ning Yu, Zeyuan Chen, Huan Wang, Silvio Savarese, Stefano Ermon, Caiming Xiong, Ran Xu:
HIVE: Harnessing Human Feedback for Instructional Visual Editing. CoRR abs/2303.09618 (2023) - [i214]Can Qin, Ning Yu, Chen Xing, Shu Zhang, Zeyuan Chen, Stefano Ermon, Yun Fu, Caiming Xiong, Ran Xu:
GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation. CoRR abs/2303.10056 (2023) - [i213]Bram Wallace, Akash Gokul, Stefano Ermon, Nikhil Naik:
End-to-End Diffusion Latent Optimization Improves Classifier Guidance. CoRR abs/2303.13703 (2023) - [i212]Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz:
Ideal Abstractions for Decision-Focused Learning. CoRR abs/2303.17062 (2023) - [i211]Arundhati Banerjee, Soham Phade, Stefano Ermon, Stephan Zheng:
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. CoRR abs/2304.04668 (2023) - [i210]Aaron Lou, Stefano Ermon:
Reflected Diffusion Models. CoRR abs/2304.04740 (2023) - [i209]Chenqing Hua, Sitao Luan, Minkai Xu, Rex Ying, Jie Fu, Stefano Ermon, Doina Precup:
MUDiff: Unified Diffusion for Complete Molecule Generation. CoRR abs/2304.14621 (2023) - [i208]Gengchen Mai, Ni Lao, Yutong He, Jiaming Song, Stefano Ermon:
CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations. CoRR abs/2305.01118 (2023) - [i207]Minkai Xu, Alexander S. Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec:
Geometric Latent Diffusion Models for 3D Molecule Generation. CoRR abs/2305.01140 (2023) - [i206]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:
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild. CoRR abs/2305.11147 (2023) - [i205]Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari:
Parallel Sampling of Diffusion Models. CoRR abs/2305.16317 (2023) - [i204]Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang:
MADiff: Offline Multi-agent Learning with Diffusion Models. CoRR abs/2305.17330 (2023) - [i203]Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, Chelsea Finn:
Direct Preference Optimization: Your Language Model is Secretly a Reward Model. CoRR abs/2305.18290 (2023) - [i202]Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji, Stefano Ermon:
On the Equivalence of Consistency-Type Models: Consistency Models, Consistent Diffusion Models, and Fokker-Planck Regularization. CoRR abs/2306.00367 (2023) - [i201]Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiao Xiang Zhu:
GEO-Bench: Toward Foundation Models for Earth Monitoring. CoRR abs/2306.03831 (2023) - [i200]Chris Cundy, Stefano Ermon:
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking. CoRR abs/2306.05426 (2023) - [i199]Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Callum Birch-Sykes, Michael Wornow, Aman Patel, Clayton M. Rabideau, Stefano Massaroli, Yoshua Bengio, Stefano Ermon, Stephen A. Baccus, Christopher Ré:
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. CoRR abs/2306.15794 (2023) - [i198]Gengchen Mai, Yao Xuan, Wenyun Zuo, Yutong He, Jiaming Song, Stefano Ermon, Krzysztof Janowicz, Ni Lao:
Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions. CoRR abs/2306.17624 (2023) - [i197]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i196]Jonathan Xu, Amna Elmustafa, Liya Weldegebriel, Emnet Negash, Richard Lee, Chenlin Meng, Stefano Ermon, David B. Lobell:
HarvestNet: A Dataset for Detecting Smallholder Farming Activity Using Harvest Piles and Remote Sensing. CoRR abs/2308.12061 (2023) - [i195]Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon:
Denoising Diffusion Bridge Models. CoRR abs/2309.16948 (2023) - [i194]Gengchen Mai, Ni Lao, Weiwei Sun, Yuchi Ma, Jiaming Song, Chenlin Meng, Hongxu Ma, Jinmeng Rao, Ziyuan Li, Stefano Ermon:
SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution. CoRR abs/2310.00413 (2023) - [i193]Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, Stefano Ermon:
Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion. CoRR abs/2310.02279 (2023) - [i192]Chenwei Wu, Li Erran Li, Stefano Ermon, Patrick Haffner, Rong Ge, Zaiwei Zhang:
The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-Language Models. CoRR abs/2310.02777 (2023) - [i191]Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David B. Lobell, Stefano Ermon:
GeoLLM: Extracting Geospatial Knowledge from Large Language Models. CoRR abs/2310.06213 (2023) - [i190]Aaron Lou, Chenlin Meng, Stefano Ermon:
Discrete Diffusion Language Modeling by Estimating the Ratios of the Data Distribution. CoRR abs/2310.16834 (2023) - [i189]Gabriel Nobis, Marco Aversa, Maximilian Springenberg, Michael Detzel, Stefano Ermon, Shinichi Nakajima, Roderick Murray-Smith, Sebastian Lapuschkin, Christoph Knochenhauer, Luis Oala, Wojciech Samek:
Generative Fractional Diffusion Models. CoRR abs/2310.17638 (2023) - [i188]Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. CoRR abs/2310.18780 (2023) - [i187]Aaron Lou, Minkai Xu, Stefano Ermon:
Scaling Riemannian Diffusion Models. CoRR abs/2310.20030 (2023) - [i186]Charles Marx, Sofian Zalouk, Stefano Ermon:
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics. CoRR abs/2310.20211 (2023) - [i185]Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Benita Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Li Fei-Fei, Jiajun Wu, Stefano Ermon, Percy Liang:
Holistic Evaluation of Text-To-Image Models. CoRR abs/2311.04287 (2023) - [i184]Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik:
Diffusion Model Alignment Using Direct Preference Optimization. CoRR abs/2311.12908 (2023) - [i183]Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J. Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon:
Manifold Preserving Guided Diffusion. CoRR abs/2311.16424 (2023) - [i182]Linqi Zhou, Andy Shih, Chenlin Meng, Stefano Ermon:
DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling. CoRR abs/2311.17082 (2023) - 2022
- [c199]Chenlin Meng, Enci Liu, Willie Neiswanger, Jiaming Song, Marshall Burke, David B. Lobell, Stefano Ermon:
IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling. AAAI 2022: 12034-12042 - [c198]Kristy Choi, Chenlin Meng, Yang Song, Stefano Ermon:
Density Ratio Estimation via Infinitesimal Classification. AISTATS 2022: 2552-2573 - [c197]Shuvam Chakraborty, Burak Uzkent, Kumar Ayush, Kumar Tanmay, Evan Sheehan, Stefano Ermon:
Efficient Conditional Pre-training for Transfer Learning. CVPR Workshops 2022: 4240-4249 - [c196]Amna Elmustafa, Erik Rozi, Yutong He, Gengchen Mai, Stefano Ermon, Marshall Burke, David B. Lobell:
Understanding economic development in rural Africa using satellite imagery, building footprints and deep models. SIGSPATIAL/GIS 2022: 89:1-89:4 - [c195]Gengchen Mai, Chris Cundy, Kristy Choi, Yingjie Hu, Ni Lao, Stefano Ermon:
Towards a foundation model for geospatial artificial intelligence (vision paper). SIGSPATIAL/GIS 2022: 106:1-106:4 - [c194]Andy Shih, Stefano Ermon, Dorsa Sadigh:
Conditional Imitation Learning for Multi-Agent Games. HRI 2022: 166-175 - [c193]Yang Song, Liyue Shen, Lei Xing, Stefano Ermon:
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models. ICLR 2022 - [c192]Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger:
An Experimental Design Perspective on Model-Based Reinforcement Learning. ICLR 2022 - [c191]Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon:
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. ICLR 2022 - [c190]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. ICLR 2022 - [c189]Shengjia Zhao, Abhishek Sinha, Yutong He, Aidan Perreault, Jiaming Song, Stefano Ermon:
Comparing Distributions by Measuring Differences that Affect Decision Making. ICLR 2022 - [c188]Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani:
Imitation Learning by Estimating Expertise of Demonstrators. ICML 2022: 1732-1748 - [c187]Charles Marx, Shengjia Zhao, Willie Neiswanger, Stefano Ermon:
Modular Conformal Calibration. ICML 2022: 15180-15195 - [c186]Chenlin Meng, Linqi Zhou, Kristy Choi, Tri Dao, Stefano Ermon:
ButterflyFlow: Building Invertible Layers with Butterfly Matrices. ICML 2022: 15360-15375 - [c185]Rui Shu, Stefano Ermon:
Bit Prioritization in Variational Autoencoders via Progressive Coding. ICML 2022: 20141-20155 - [c184]Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon:
A General Recipe for Likelihood-free Bayesian Optimization. ICML 2022: 20384-20404 - [c183]Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon:
Experience Replay with Likelihood-free Importance Weights. L4DC 2022: 110-123 - [c182]Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon:
SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery. NeurIPS 2022 - [c181]Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré:
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. NeurIPS 2022 - [c180]Yann Dubois, Stefano Ermon, Tatsunori B. Hashimoto, Percy Liang:
Improving Self-Supervised Learning by Characterizing Idealized Representations. NeurIPS 2022 - [c179]Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon:
LISA: Learning Interpretable Skill Abstractions from Language. NeurIPS 2022 - [c178]Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song:
Denoising Diffusion Restoration Models. NeurIPS 2022 - [c177]Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. NeurIPS 2022 - [c176]Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark D. Boyer, Stefano Ermon, Jeff Schneider, Willie Neiswanger:
Exploration via Planning for Information about the Optimal Trajectory. NeurIPS 2022 - [c175]Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon:
Concrete Score Matching: Generalized Score Matching for Discrete Data. NeurIPS 2022 - [c174]Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon:
Generalizing Bayesian Optimization with Decision-theoretic Entropies. NeurIPS 2022 - [c173]Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon:
Transform Once: Efficient Operator Learning in Frequency Domain. NeurIPS 2022 - [c172]Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon:
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. NeurIPS 2022 - [c171]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Training and Inference on Any-Order Autoregressive Models the Right Way. NeurIPS 2022 - [c170]Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone:
Local calibration: metrics and recalibration. UAI 2022: 1286-1295 - [i181]Andy Shih, Stefano Ermon, Dorsa Sadigh:
Conditional Imitation Learning for Multi-Agent Games. CoRR abs/2201.01448 (2022) - [i180]Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song:
Denoising Diffusion Restoration Models. CoRR abs/2201.11793 (2022) - [i179]Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani:
Imitation Learning by Estimating Expertise of Demonstrators. CoRR abs/2202.01288 (2022) - [i178]Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon:
LISA: Learning Interpretable Skill Abstractions from Language. CoRR abs/2203.00054 (2022) - [i177]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation. CoRR abs/2203.02923 (2022) - [i176]Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon:
Dual Diffusion Implicit Bridges for Image-to-Image Translation. CoRR abs/2203.08382 (2022) - [i175]Benedikt Boecking, Willie Neiswanger, Nicholas Carl Roberts, Stefano Ermon, Frederic Sala, Artur Dubrawski:
Generative Modeling Helps Weak Supervision (and Vice Versa). CoRR abs/2203.12023 (2022) - [i174]Yutong He, William Zhang, Chenlin Meng, Marshall Burke, David B. Lobell, Stefano Ermon:
Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution. CoRR abs/2204.01736 (2022) - [i173]Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon:
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. CoRR abs/2204.07673 (2022) - [i172]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Training and Inference on Any-Order Autoregressive Models the Right Way. CoRR abs/2205.13554 (2022) - [i171]Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré:
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. CoRR abs/2205.14135 (2022) - [i170]Charles Marx, Shengjia Zhou, Willie Neiswanger, Stefano Ermon:
Modular Conformal Calibration. CoRR abs/2206.11468 (2022) - [i169]Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon:
A General Recipe for Likelihood-free Bayesian Optimization. CoRR abs/2206.13035 (2022) - [i168]Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon:
SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery. CoRR abs/2207.08051 (2022) - [i167]Sara A. Miskovich, Willie Neiswanger, William Colocho, Claudio Emma, Jacqueline Garrahan, Timothy Maxwell, Christopher Mayes, Stefano Ermon, Auralee Edelen, Daniel Ratner:
Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements. CoRR abs/2209.04587 (2022) - [i166]Yann Dubois, Tatsunori Hashimoto, Stefano Ermon, Percy Liang:
Improving Self-Supervised Learning by Characterizing Idealized Representations. CoRR abs/2209.06235 (2022) - [i165]Bahjat Kawar, Jiaming Song, Stefano Ermon, Michael Elad:
JPEG Artifact Correction using Denoising Diffusion Restoration Models. CoRR abs/2209.11888 (2022) - [i164]Chenlin Meng, Linqi Zhou, Kristy Choi, Tri Dao, Stefano Ermon:
ButterflyFlow: Building Invertible Layers with Butterfly Matrices. CoRR abs/2209.13774 (2022) - [i163]Gengchen Mai, Chiyu Jiang, Weiwei Sun, Rui Zhu, Yao Xuan, Ling Cai, Krzysztof Janowicz, Stefano Ermon, Ni Lao:
Towards General-Purpose Representation Learning of Polygonal Geometries. CoRR abs/2209.15458 (2022) - [i162]