Stefano Ermon

According to our database1, Stefano Ermon authored at least 117 papers between 2009 and 2018.

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2018
Multi-Agent Generative Adversarial Imitation Learning.
CoRR, 2018

Improved Training with Curriculum GANs.
CoRR, 2018

Modeling Sparse Deviations for Compressed Sensing using Generative Models.
CoRR, 2018

Accurate Uncertainties for Deep Learning Using Calibrated Regression.
CoRR, 2018

The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models.
CoRR, 2018

Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning.
CoRR, 2018

Adversarial Constraint Learning for Structured Prediction.
CoRR, 2018

Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance.
CoRR, 2018

Amortized Inference Regularization.
CoRR, 2018

Generative Adversarial Examples.
CoRR, 2018

Tile2Vec: Unsupervised representation learning for spatially distributed data.
CoRR, 2018

Variational Rejection Sampling.
CoRR, 2018

End-to-End Learning of Motion Representation for Video Understanding.
CoRR, 2018

Best arm identification in multi-armed bandits with delayed feedback.
CoRR, 2018

Graphite: Iterative Generative Modeling of Graphs.
CoRR, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
CoRR, 2018

A DIRT-T Approach to Unsupervised Domain Adaptation.
CoRR, 2018

Approximate Inference via Weighted Rademacher Complexity.
CoRR, 2018

Learning with Weak Supervision from Physics and Data-Driven Constraints.
AI Magazine, 2018

Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Adversarial Constraint Learning for Structured Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
Proceedings of the 35th International Conference on Machine Learning, 2018

Accurate Uncertainties for Deep Learning Using Calibrated Regression.
Proceedings of the 35th International Conference on Machine Learning, 2018

Modeling Sparse Deviations for Compressed Sensing using Generative Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Deep Transfer Learning for Crop Yield Prediction with Remote Sensing Data.
Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, 2018

Best arm identification in multi-armed bandits with delayed feedback.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Variational Rejection Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Deterministic Policy Optimization by Combining Pathwise and Score Function Estimators for Discrete Action Spaces.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Approximate Inference via Weighted Rademacher Complexity.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Boosted Generative Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Shape optimization in laminar flow with a label-guided variational autoencoder.
CoRR, 2017

Deterministic Policy Optimization by Combining Pathwise and Score Function Estimators for Discrete Action Spaces.
CoRR, 2017

Hierarchical Modeling of Seed Variety Yields and Decision Making for Future Planting Plans.
CoRR, 2017

Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning.
CoRR, 2017

Neural Variational Inference and Learning in Undirected Graphical Models.
CoRR, 2017

PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples.
CoRR, 2017

A Survey of Human Activity Recognition Using WiFi CSI.
CoRR, 2017

Audio Super Resolution using Neural Networks.
CoRR, 2017

InfoVAE: Information Maximizing Variational Autoencoders.
CoRR, 2017

Towards Deeper Understanding of Variational Autoencoding Models.
CoRR, 2017

Learning Hierarchical Features from Generative Models.
CoRR, 2017

General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis.
CoRR, 2017

A-NICE-MC: Adversarial Training for MCMC.
CoRR, 2017

On the Limits of Learning Representations with Label-Based Supervision.
CoRR, 2017

Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search.
CoRR, 2017

Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs.
CoRR, 2017

Boosted Generative Models.
CoRR, 2017

Flow-GAN: Bridging implicit and prescribed learning in generative models.
CoRR, 2017

A Survey on Behavior Recognition Using WiFi Channel State Information.
IEEE Communications Magazine, 2017

Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Hybrid Deep Discriminative/Generative Models for Semi-Supervised Learning.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Stencil Autotuning with Ordinal Regression: Extended Abstract.
Proceedings of the 20th International Workshop on Software and Compilers for Embedded Systems, 2017

A-NICE-MC: Adversarial Training for MCMC.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Neural Variational Inference and Learning in Undirected Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Autotuning Stencil Computations with Structural Ordinal Regression Learning.
Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

Learning Hierarchical Features from Deep Generative Models.
Proceedings of the 34th International Conference on Machine Learning, 2017

Monitoring Ethiopian Wheat Fungus with Satellite Imagery and Deep Feature Learning.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Label-Free Supervision of Neural Networks with Physics and Domain Knowledge.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Estimating Uncertainty Online Against an Adversary.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Solving Marginal MAP Problems with NP Oracles and Parity Constraints.
CoRR, 2016

Label-Free Supervision of Neural Networks with Physics and Domain Knowledge.
CoRR, 2016

Reliable Confidence Estimation via Online Learning.
CoRR, 2016

Model-Free Imitation Learning with Policy Optimization.
CoRR, 2016

Generative Adversarial Imitation Learning.
CoRR, 2016

Sparse Gaussian Processes for Bayesian Optimization.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Adaptive Concentration Inequalities for Sequential Decision Problems.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Solving Marginal MAP Problems with NP Oracles and Parity Constraints.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Generative Adversarial Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variational Bayes on Monte Carlo Steroids.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variable Elimination in the Fourier Domain.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning and Inference via Maximum Inner Product Search.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Model-Free Imitation Learning with Policy Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Tight Variational Bounds via Random Projections and I-Projections.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Closing the Gap Between Short and Long XORs for Model Counting.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Exact Sampling with Integer Linear Programs and Random Perturbations.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Closing the Gap Between Short and Long XORs for Model Counting.
CoRR, 2015

Variable Elimination in Fourier Domain.
CoRR, 2015

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping.
CoRR, 2015

Tight Variational Bounds via Random Projections and I-Projections.
CoRR, 2015

Importance Sampling over Sets: A New Probabilistic Inference Scheme.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem: Application to Materials Discovery.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

A Hybrid Approach for Probabilistic Inference using Random Projections.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem.
Proceedings of the Computational Sustainability, 2015

Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Pattern Decomposition with Complex Combinatorial Constraints: Application to Materials Discovery.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Pattern Decomposition with Complex Combinatorial Constraints: Application to Materials Discovery.
CoRR, 2014

Low-density Parity Constraints for Hashing-Based Discrete Integration.
Proceedings of the 31th International Conference on Machine Learning, 2014

Uncovering Hidden Structure through Parallel Problem Decomposition.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Designing Fast Absorbing Markov Chains.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Learning policies for battery usage optimization in electric vehicles.
Machine Learning, 2013

Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization
CoRR, 2013

Optimization With Parity Constraints: From Binary Codes to Discrete Integration.
CoRR, 2013

Optimization With Parity Constraints: From Binary Codes to Discrete Integration.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Embed and Project: Discrete Sampling with Universal Hashing.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Uniform Solution Sampling Using a Constraint Solver As an Oracle
CoRR, 2012

Playing games against nature: optimal policies for renewable resource allocation
CoRR, 2012

Uniform Solution Sampling Using a Constraint Solver As an Oracle.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

SMT-Aided Combinatorial Materials Discovery.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2012, 2012

Feature-Enhanced Probabilistic Models for Diffusion Network Inference.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Learning Policies for Battery Usage Optimization in Electric Vehicles.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Density Propagation and Improved Bounds on the Partition Function.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Probabilistic planning with non-linear utility functions and worst-case guarantees.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011
Accelerated Adaptive Markov Chain for Partition Function Computation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A Flat Histogram Method for Computing the Density of States of Combinatorial Problems.
Proceedings of the IJCAI 2011, 2011

Risk-Sensitive Policies for Sustainable Renewable Resource Allocation.
Proceedings of the IJCAI 2011, 2011

A message passing approach to multiagent gaussian inference for dynamic processes.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

2010
Playing games against nature: optimal policies for renewable resource allocation.
Proceedings of the UAI 2010, 2010

Computing the Density of States of Boolean Formulas.
Proceedings of the Principles and Practice of Constraint Programming - CP 2010, 2010

Collaborative multiagent Gaussian inference in a dynamic environment using belief propagation.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

2009
Trust Estimation in autonomic networks: a statistical mechanics approach.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009


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