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Stefano Ermon
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- affiliation: Stanford University
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2020 – today
- 2024
- [j12]Sara A. Miskovich, Willie Neiswanger, William Colocho, Claudio Emma, Jacqueline Garrahan, Timothy Maxwell, Christopher Mayes, Stefano Ermon, Auralee Edelen, Daniel Ratner:
Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives. Mach. Learn. Sci. Technol. 5(1): 15004 (2024) - [c255]Tailin Wu, Willie Neiswanger, Hongtao Zheng, Stefano Ermon, Jure Leskovec:
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution. AAAI 2024: 320-328 - [c254]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. AAAI 2024: 22438-22446 - [c253]Ryan Park, Rafael Rafailov, Stefano Ermon, Chelsea Finn:
Disentangling Length from Quality in Direct Preference Optimization. ACL (Findings) 2024: 4998-5017 - [c252]Chris Cundy, Rishi Desai, Stefano Ermon:
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients. AISTATS 2024: 2809-2817 - [c251]Linqi Zhou, Andy Shih, Chenlin Meng, Stefano Ermon:
DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling. CVPR 2024: 4610-4619 - [c250]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. CVPR Workshops 2024: 5366-5374 - [c249]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. CVPR 2024: 8228-8238 - [c248]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. CVPR 2024: 9026-9036 - [c247]Hao Li, Yang Zou, Ying Wang, Orchid Majumder, Yusheng Xie, R. Manmatha, Ashwin Swaminathan, Zhuowen Tu, Stefano Ermon, Stefano Soatto:
On the Scalability of Diffusion-based Text-to-Image Generation. CVPR 2024: 9400-9409 - [c246]Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui:
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing. ICLR 2024 - [c245]Chris Cundy, Stefano Ermon:
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking. ICLR 2024 - [c244]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. ICLR 2024 - [c243]Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David B. Lobell, Stefano Ermon:
DiffusionSat: A Generative Foundation Model for Satellite Imagery. ICLR 2024 - [c242]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. ICLR 2024 - [c241]Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David B. Lobell, Stefano Ermon:
GeoLLM: Extracting Geospatial Knowledge from Large Language Models. ICLR 2024 - [c240]Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D. Manning, Chelsea Finn, Stefano Ermon:
Language Model Detectors Are Easily Optimized Against. ICLR 2024 - [c239]Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon:
Denoising Diffusion Bridge Models. ICLR 2024 - [c238]Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui:
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs. ICML 2024 - [c237]Aaron Lou, Chenlin Meng, Stefano Ermon:
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution. ICML 2024 - [c236]Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, Stefano Ermon:
Large Language Models are Geographically Biased. ICML 2024 - [c235]Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Michael Poli, Atsushi Yamashita:
State-Free Inference of State-Space Models: The *Transfer Function* Approach. ICML 2024 - [c234]Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli:
Mechanistic Design and Scaling of Hybrid Architectures. ICML 2024 - [c233]Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar:
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. ICML 2024 - [c232]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML 2024 - [i248]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR abs/2401.11037 (2024) - [i247]Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui:
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs. CoRR abs/2401.11708 (2024) - [i246]Zhuo Zheng, Yanfei Zhong, Liangpei Zhang, Stefano Ermon:
Segment Any Change. CoRR abs/2402.01188 (2024) - [i245]Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, Stefano Ermon:
Large Language Models are Geographically Biased. CoRR abs/2402.02680 (2024) - [i244]Tailin Wu, Willie Neiswanger, Hongtao Zheng, Stefano Ermon, Jure Leskovec:
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution. CoRR abs/2402.08383 (2024) - [i243]Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui:
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing. CoRR abs/2402.16627 (2024) - [i242]Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli:
Mechanistic Design and Scaling of Hybrid Architectures. CoRR abs/2403.17844 (2024) - [i241]Ryan Park, Rafael Rafailov, Stefano Ermon, Chelsea Finn:
Disentangling Length from Quality in Direct Preference Optimization. CoRR abs/2403.19159 (2024) - [i240]Hao Li, Yang Zou, Ying Wang, Orchid Majumder, Yusheng Xie, R. Manmatha, Ashwin Swaminathan, Zhuowen Tu, Stefano Ermon, Stefano Soatto:
On the Scalability of Diffusion-based Text-to-Image Generation. CoRR abs/2404.02883 (2024) - [i239]Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar:
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. CoRR abs/2404.14367 (2024) - [i238]Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Atsushi Yamashita, Michael Poli:
State-Free Inference of State-Space Models: The Transfer Function Approach. CoRR abs/2405.06147 (2024) - [i237]Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon:
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher. CoRR abs/2405.14822 (2024) - [i236]Samar Khanna, Medhanie Irgau, David B. Lobell, Stefano Ermon:
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts. CoRR abs/2406.10973 (2024) - [i235]Nemin Wu, Qian Cao, Zhangyu Wang, Zeping Liu, Yanlin Qi, Jielu Zhang, Joshua Ni, Xiaobai Yao, Hongxu Ma, Lan Mu, Stefano Ermon, Tanuja Ganu, Akshay Nambi, Ni Lao, Gengchen Mai:
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning. CoRR abs/2406.15658 (2024) - [i234]Zhuo Zheng, Stefano Ermon, Dongjun Kim, Liangpei Zhang, Yanfei Zhong:
Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model. CoRR abs/2406.17998 (2024) - [i233]Siyi Gu, Minkai Xu, Alexander S. Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon:
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. CoRR abs/2407.01648 (2024) - [i232]Ling Yang, Zixiang Zhang, Zhilong Zhang, Xingchao Liu, Minkai Xu, Wentao Zhang, Chenlin Meng, Stefano Ermon, Bin Cui:
Consistency Flow Matching: Defining Straight Flows with Velocity Consistency. CoRR abs/2407.02398 (2024) - [i231]Eunwoo Kim, Un Yang, Cheol Lae Roh, Stefano Ermon:
Unsupervised Anomaly Detection Using Diffusion Trend Analysis. CoRR abs/2407.09578 (2024) - [i230]Syrine Belakaria, Benjamin Letham, Janardhan Rao Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy:
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. CoRR abs/2407.09739 (2024) - [i229]Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Stefano Ermon:
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion. CoRR abs/2409.07025 (2024) - [i228]Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Zou, Stefano Ermon:
TFG: Unified Training-Free Guidance for Diffusion Models. CoRR abs/2409.15761 (2024) - [i227]Charles Marx, Volodymyr Kuleshov, Stefano Ermon:
Calibrated Probabilistic Forecasts for Arbitrary Sequences. CoRR abs/2409.19157 (2024) - [i226]Yangming Li, Chieh-Hsin Lai, Carola-Bibiane Schönlieb, Yuki Mitsufuji, Stefano Ermon:
Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space. CoRR abs/2410.01796 (2024) - [i225]Rohin Manvi, Anikait Singh, Stefano Ermon:
Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation. CoRR abs/2410.02725 (2024) - 2023
- [j11]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) - [j10]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) - [j9]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) - [j8]Arundhati Banerjee, Soham R. Phade, Stefano Ermon, Stephan Zheng:
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j7]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu:
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Trans. Mach. Learn. Res. 2023 (2023) - [c231]Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon:
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching. AAAI 2023: 11016-11024 - [c230]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 - [c229]Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz:
Ideal Abstractions for Decision-Focused Learning. AISTATS 2023: 10223-10234 - [c228]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 - [c227]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. ICBINB 2023: 118-126 - [c226]Bram Wallace, Akash Gokul, Stefano Ermon, Nikhil Naik:
End-to-End Diffusion Latent Optimization Improves Classifier Guidance. ICCV 2023: 7246-7256 - [c225]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. ICCV 2023: 23028-23039 - [c224]Benedikt Boecking, Nicholas Carl Roberts, Willie Neiswanger, Stefano Ermon, Frederic Sala, Artur Dubrawski:
Generative Modeling Helps Weak Supervision (and Vice Versa). ICLR 2023 - [c223]Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon:
Extreme Q-Learning: MaxEnt RL without Entropy. ICLR 2023 - [c222]Kuno Kim, Stefano Ermon:
Understanding and Adopting Rational Behavior by Bellman Score Estimation. ICLR 2023 - [c221]Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon:
Dual Diffusion Implicit Bridges for Image-to-Image Translation. ICLR 2023 - [c220]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 - [c219]Aaron Lou, Stefano Ermon:
Reflected Diffusion Models. ICML 2023: 22675-22701 - [c218]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 - [c217]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 - [c216]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 - [c215]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Long Horizon Temperature Scaling. ICML 2023: 31422-31434 - [c214]Minkai Xu, Alexander S. Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec:
Geometric Latent Diffusion Models for 3D Molecule Generation. ICML 2023: 38592-38610 - [c213]Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon:
Deep Latent State Space Models for Time-Series Generation. ICML 2023: 42625-42643 - [c212]Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon:
Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834 - [c211]Chenqing Hua, Sitao Luan, Minkai Xu, Zhitao Ying, Jie Fu, Stefano Ermon, Doina Precup:
MUDiff: Unified Diffusion for Complete Molecule Generation. LoG 2023: 33 - [c210]Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu:
GEO-Bench: Toward Foundation Models for Earth Monitoring. NeurIPS 2023 - [c209]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:
Holistic Evaluation of Text-to-Image Models. NeurIPS 2023 - [c208]Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon:
Scaling Riemannian Diffusion Models. NeurIPS 2023 - [c207]Charlie Marx, Sofian Zalouk, Stefano Ermon:
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics. NeurIPS 2023 - [c206]Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. NeurIPS 2023 - [c205]Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton M. Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Ré, Stephen Baccus:
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. NeurIPS 2023 - [c204]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. NeurIPS 2023 - [c203]Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, Chelsea Finn:
Direct Preference Optimization: Your Language Model is Secretly a Reward Model. NeurIPS 2023 - [c202]Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari:
Parallel Sampling of Diffusion Models. NeurIPS 2023 - [c201]Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma:
Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation. NeurIPS 2023 - [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 - [i224]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) - [i223]Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon:
Extreme Q-Learning: MaxEnt RL without Entropy. CoRR abs/2301.02328 (2023) - [i222]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) - [i221]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Long Horizon Temperature Scaling. CoRR abs/2302.03686 (2023) - [i220]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) - [i219]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) - [i218]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) - [i217]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) - [i216]Bram Wallace, Akash Gokul, Stefano Ermon, Nikhil Naik:
End-to-End Diffusion Latent Optimization Improves Classifier Guidance. CoRR abs/2303.13703 (2023) - [i215]Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz:
Ideal Abstractions for Decision-Focused Learning. CoRR abs/2303.17062 (2023) - [i214]Arundhati Banerjee, Soham Phade, Stefano Ermon, Stephan Zheng:
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. CoRR abs/2304.04668 (2023) - [i213]Aaron Lou, Stefano Ermon:
Reflected Diffusion Models. CoRR abs/2304.04740 (2023) - [i212]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) - [i211]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) - [i210]Minkai Xu, Alexander S. Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec:
Geometric Latent Diffusion Models for 3D Molecule Generation. CoRR