Stefano Ermon
Identifiers
- name variant Stefano Ermon 0.60 · backfill
Papers (90)
- Mitigating Bias in Locally Constrained Decoding via Tractable Proposals cs.CL · 2026 · author #6
- Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models cs.LG · 2026 · author #3
- One-Step Generative Modeling via Wasserstein Gradient Flows cs.LG · 2026 · author #5
- Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations cs.AI · 2026 · author #9
- Generative Modeling with Flux Matching cs.LG · 2026 · author #3
- ABC: Any-Subset Autoregression via Non-Markovian Diffusion Bridges in Continuous Time and Space cs.LG · 2026 · author #5
- A satellite foundation model for improved wealth monitoring cs.CY · 2026 · author #6
- Evaluation-driven Scaling for Scientific Discovery cs.LG · 2026 · author #21
- Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics cs.LG · 2026 · author #6
- A Unified View of Score-Based and Drifting Models cs.LG · 2026 · author #7
- GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning cs.LG · 2026 · author #6
- Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation cs.LG · 2025 · author #6
- Generative Modeling Enables Molecular Structure Retrieval from Coulomb Explosion Imaging physics.chem-ph · 2025 · author #14
- The Principles of Diffusion Models cs.LG · 2025 · author #5
- DiffusionNFT: Online Diffusion Reinforcement with Forward Process cs.LG · 2025 · author #8
- Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement cs.LG · 2025 · author #6
- Mercury: Ultra-Fast Language Models Based on Diffusion cs.CL · 2025 · author #11
- FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users cs.LG · 2025 · author #5
- Humanity's Last Exam cs.LG · 2025 · author #915
- Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution stat.ML · 2023 · author #3
- Direct Preference Optimization: Your Language Model is Secretly a Reward Model cs.LG · 2023 · author #4
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models cs.CL · 2022 · author #386
- FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness cs.LG · 2022 · author #3
- On the Opportunities and Risks of Foundation Models cs.LG · 2021 · author #23
- SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations cs.CV · 2021 · author #7
- Score-Based Generative Modeling through Stochastic Differential Equations cs.LG · 2020 · author #5
- Denoising Diffusion Implicit Models cs.LG · 2020 · author #3
- Generative Modeling by Estimating Gradients of the Data Distribution cs.LG · 2019 · author #2
- Calibrated Model-Based Deep Reinforcement Learning cs.LG · 2019 · author #6
- Sliced Score Matching: A Scalable Approach to Density and Score Estimation cs.LG · 2019 · author #4
- Predicting Economic Development using Geolocated Wikipedia Articles cs.LG · 2019 · author #8
- Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery cs.CV · 2019 · author #9
- Distributed generation of privacy preserving data with user customization cs.LG · 2019 · author #3
- Stochastic Optimization of Sorting Networks via Continuous Relaxations stat.ML · 2019 · author #4
- Training Variational Autoencoders with Buffered Stochastic Variational Inference stat.ML · 2019 · author #4
- Semi-Supervised Multitask Learning on Multispectral Satellite Images Using Wasserstein Generative Adversarial Networks (GANs) for Predicting Poverty cs.CV · 2019 · author #3
- Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization stat.ML · 2018 · author #2
- Neural Joint Source-Channel Coding cs.LG · 2018 · author #5
- Bias and Generalization in Deep Generative Models: An Empirical Study cs.LG · 2018 · author #6
- Learning to Interpret Satellite Images Using Wikipedia cs.CV · 2018 · author #7
- Multi-Agent Generative Adversarial Imitation Learning cs.LG · 2018 · author #4
- Improved Training with Curriculum GANs cs.LG · 2018 · author #3
- Modeling Sparse Deviations for Compressed Sensing using Generative Models stat.ML · 2018 · author #3
- Accurate Uncertainties for Deep Learning Using Calibrated Regression cs.LG · 2018 · author #3
- The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models stat.ML · 2018 · author #3
- Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning cs.CY · 2018 · author #9
- Adversarial Constraint Learning for Structured Prediction cs.LG · 2018 · author #5
- Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance cs.LG · 2018 · author #3
- Amortized Inference Regularization stat.ML · 2018 · author #5
- Constructing Unrestricted Adversarial Examples with Generative Models cs.LG · 2018 · author #4
- Tile2Vec: Unsupervised representation learning for spatially distributed data cs.CV · 2018 · author #6
- Variational Rejection Sampling stat.ML · 2018 · author #5
- End-to-End Learning of Motion Representation for Video Understanding cs.CV · 2018 · author #4
- Best arm identification in multi-armed bandits with delayed feedback cs.LG · 2018 · author #11
- Graphite: Iterative Generative Modeling of Graphs stat.ML · 2018 · author #3
- Accelerating Natural Gradient with Higher-Order Invariance cs.LG · 2018 · author #3
- A DIRT-T Approach to Unsupervised Domain Adaptation stat.ML · 2018 · author #4
- Approximate Inference via Weighted Rademacher Complexity cs.LG · 2018 · author #3
- Shape optimization in laminar flow with a label-guided variational autoencoder cs.CE · 2017 · author #3
- Deterministic Policy Optimization by Combining Pathwise and Score Function Estimators for Discrete Action Spaces cs.AI · 2017 · author #2
- Hierarchical Modeling of Seed Variety Yields and Decision Making for Future Planting Plans cs.LG · 2017 · author #4
- Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning stat.ML · 2017 · author #6
- Neural Variational Inference and Learning in Undirected Graphical Models cs.LG · 2017 · author #2
- PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples cs.LG · 2017 · author #4
- A Survey of Human Activity Recognition Using WiFi CSI cs.AI · 2017 · author #4
- Audio Super Resolution using Neural Networks cs.SD · 2017 · author #3
- Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search cs.LG · 2017 · author #3
- A-NICE-MC: Adversarial Training for MCMC stat.ML · 2017 · author #3
- InfoVAE: Information Maximizing Variational Autoencoders cs.LG · 2017 · author #3
- Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models cs.LG · 2017 · author #3
- InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations cs.LG · 2017 · author #3
- On the Limits of Learning Representations with Label-Based Supervision cs.LG · 2017 · author #4
- Towards Deeper Understanding of Variational Autoencoding Models cs.LG · 2017 · author #3
- Boosted Generative Models cs.LG · 2017 · author #2
- Learning Hierarchical Features from Generative Models cs.LG · 2017 · author #3
- General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis cs.DM · 2017 · author #2
- Solving Marginal MAP Problems with NP Oracles and Parity Constraints cs.AI · 2016 · author #3
- Label-Free Supervision of Neural Networks with Physics and Domain Knowledge cs.AI · 2016 · author #2
- Estimating Uncertainty Online Against an Adversary cs.LG · 2016 · author #2
- Generative Adversarial Imitation Learning cs.LG · 2016 · author #2
- Model-Free Imitation Learning with Policy Optimization cs.LG · 2016 · author #3
- Closing the Gap Between Short and Long XORs for Model Counting cs.CC · 2015 · author #4
- Tight Variational Bounds via Random Projections and I-Projections cs.LG · 2015 · author #3
- Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping cs.CV · 2015 · author #5
- Variable Elimination in the Fourier Domain cs.AI · 2015 · author #2
- Pattern Decomposition with Complex Combinatorial Constraints: Application to Materials Discovery cs.AI · 2014 · author #1
- Optimization With Parity Constraints: From Binary Codes to Discrete Integration cs.AI · 2013 · author #1
- Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization cs.LG · 2013 · author #1
- Uniform Solution Sampling Using a Constraint Solver As an Oracle cs.AI · 2012 · author #1
- Playing games against nature: optimal policies for renewable resource allocation cs.AI · 2012 · author #1
Mentions
- 2606.01926 #6 · arxiv_oai · confidence 0.70 Stefano Ermon
- 2601.22651 #6 · arxiv_oai · confidence 0.70 Stefano Ermon
- 1411.7441 #1 · backfill · confidence 0.70 Stefano Ermon
- 1309.6827 #1 · backfill · confidence 0.70 Stefano Ermon
- 2605.11755 #5 · arxiv_oai · confidence 0.70 Stefano Ermon
- 2605.26491 #3 · arxiv_oai · confidence 0.70 Stefano Ermon
- 1302.6677 #1 · backfill · confidence 0.70 Stefano Ermon
- 1210.4861 #1 · backfill · confidence 0.70 Stefano Ermon
- 1203.3478 #1 · backfill · confidence 0.70 Stefano Ermon
- 2603.07514 #7 · arxiv_oai · confidence 0.70 Stefano Ermon
- 2510.21890 #5 · arxiv_oai · confidence 0.70 Stefano Ermon
- 1907.05600 #2 · arxiv_oai · confidence 0.70 Stefano Ermon
- 2506.17298 #11 · arxiv_oai · confidence 0.70 Stefano Ermon
Frequent Coauthors
- Jiaming Song 15 shared papers
- Aditya Grover 10 shared papers
- David Lobell 9 shared papers
- Shengjia Zhao 9 shared papers
- Marshall Burke 8 shared papers
- Yang Song 8 shared papers
- Bart Selman 7 shared papers
- Volodymyr Kuleshov 7 shared papers
- Carla P. Gomes 6 shared papers
- Chenlin Meng 6 shared papers
- Jiaqi Han 6 shared papers
- Ashish Sabharwal 5 shared papers
- Hongyu Ren 4 shared papers
- Neal Jean 4 shared papers
- Rui Shu 4 shared papers
- Chelsea Finn 3 shared papers
- Chieh-Hsin Lai 3 shared papers
- Christopher D. Manning 3 shared papers
- Daniel Levy 3 shared papers
- Eric Mitchell 3 shared papers