Stefano Ermon
According to our database^{1},
Stefano Ermon
authored at least 89 papers
between 2009 and 2019.
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Bibliography
2019
MultiAgent Adversarial Inverse Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019
Adaptive Antithetic Sampling for Variance Reduction.
Proceedings of the 36th International Conference on Machine Learning, 2019
Calibrated ModelBased Deep Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019
Graphite: Iterative Generative Modeling of Graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019
Neural Joint SourceChannel Coding.
Proceedings of the 36th International Conference on Machine Learning, 2019
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Learning Controllable Fair Representations.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Training Variational Autoencoders with Buffered Stochastic Variational Inference.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Learning with Weak Supervision from Physics and DataDriven Constraints.
AI Magazine, 2018
A Lagrangian Perspective on Latent Variable Generative Models.
Proceedings of the ThirtyFourth Conference on Uncertainty in Artificial Intelligence, 2018
Bayesian optimization and attribute adjustment.
Proceedings of the ThirtyFourth Conference on Uncertainty in Artificial Intelligence, 2018
Bias and Generalization in Deep Generative Models: An Empirical Study.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Constructing Unrestricted Adversarial Examples with Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
MultiAgent Generative Adversarial Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Amortized Inference Regularization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Semisupervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Streamlining Variational Inference for Constraint Satisfaction Problems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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 TwentySeventh International Joint Conference on Artificial Intelligence, 2018
Accelerating Natural Gradient with HigherOrder 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
MultiAgent Generative Adversarial Imitation Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018
A DIRTT Approach to Unsupervised Domain Adaptation.
Proceedings of the 6th International Conference on Learning Representations, 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
EndtoEnd Learning of Motion Representation for Video Understanding.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018
Best arm identification in multiarmed 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 ThirtySecond AAAI Conference on Artificial Intelligence, 2018
Approximate Inference via Weighted Rademacher Complexity.
Proceedings of the ThirtySecond AAAI Conference on Artificial Intelligence, 2018
Boosted Generative Models.
Proceedings of the ThirtySecond AAAI Conference on Artificial Intelligence, 2018
FlowGAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models.
Proceedings of the ThirtySecond AAAI Conference on Artificial Intelligence, 2018
2017
A Survey on Behavior Recognition Using WiFi Channel State Information.
IEEE Communications Magazine, 2017
Fast Amortized Inference and Learning in Loglinear Models with Randomly Perturbed Nearest Neighbor Search.
Proceedings of the ThirtyThird Conference on Uncertainty in Artificial Intelligence, 2017
Hybrid Deep Discriminative/Generative Models for SemiSupervised Learning.
Proceedings of the ThirtyThird 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
ANICEMC: 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
Generative Adversarial Learning of Markov Chains.
Proceedings of the 5th International Conference on Learning Representations, 2017
Audio SuperResolution using Neural Networks.
Proceedings of the 5th International Conference on Learning Representations, 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 ThirtyFirst AAAI Conference on Artificial Intelligence, 2017
General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis.
Proceedings of the ThirtyFirst AAAI Conference on Artificial Intelligence, 2017
LabelFree Supervision of Neural Networks with Physics and Domain Knowledge.
Proceedings of the ThirtyFirst AAAI Conference on Artificial Intelligence, 2017
Estimating Uncertainty Online Against an Adversary.
Proceedings of the ThirtyFirst AAAI Conference on Artificial Intelligence, 2017
2016
Sparse Gaussian Processes for Bayesian Optimization.
Proceedings of the ThirtySecond 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
ModelFree 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 IProjections.
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
Importance Sampling over Sets: A New Probabilistic Inference Scheme.
Proceedings of the ThirtyFirst 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 TwentyFourth 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 LargeScale Dynamic Discrete Choice Models of SpatioTemporal Preferences with Application to Migratory Pastoralism in East Africa.
Proceedings of the TwentyNinth AAAI Conference on Artificial Intelligence, 2015
Pattern Decomposition with Complex Combinatorial Constraints: Application to Materials Discovery.
Proceedings of the TwentyNinth AAAI Conference on Artificial Intelligence, 2015
2014
Lowdensity Parity Constraints for HashingBased Discrete Integration.
Proceedings of the 31th International Conference on Machine Learning, 2014
Uncovering Hidden Structure through Parallel Problem Decomposition.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
Designing Fast Absorbing Markov Chains.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
2013
Optimization With Parity Constraints: From Binary Codes to Discrete Integration.
Proceedings of the TwentyNinth 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 58, 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.
Proceedings of the TwentyEighth Conference on Uncertainty in Artificial Intelligence, 2012
SMTAided Combinatorial Materials Discovery.
Proceedings of the Theory and Applications of Satisfiability Testing  SAT 2012, 2012
FeatureEnhanced 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 36, 2012
Probabilistic planning with nonlinear utility functions and worstcase 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 1214 December 2011, 2011
A Flat Histogram Method for Computing the Density of States of Combinatorial Problems.
Proceedings of the IJCAI 2011, 2011
RiskSensitive 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