Geography-Aware Self-Supervised Learning

Nov 21, 2020
Kumar Ayush, Burak Uzkent, Chenlin Meng, Kumar Tanmay, Marshall Burke, David Lobell, Stefano Ermon

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Efficient Conditional Pre-training for Transfer Learning

Nov 20, 2020
Shuvam Chakraborty, Burak Uzkent, Kumar Ayush, Kumar Tanmay, Evan Sheehan, Stefano Ermon

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Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration

Nov 15, 2020
Shengjia Zhao, Stefano Ermon

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Autoregressive Score Matching

Oct 24, 2020
Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon

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* NeurIPS 2020 

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Probabilistic Circuits for Variational Inference in Discrete Graphical Models

Oct 22, 2020
Andy Shih, Stefano Ermon

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* In Advances in Neural Information Processing Systems 34 (NeurIPS), 2020 

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Imitation with Neural Density Models

Oct 19, 2020
Kuno Kim, Akshat Jindal, Yang Song, Jiaming Song, Yanan Sui, Stefano Ermon

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Denoising Diffusion Implicit Models

Oct 06, 2020
Jiaming Song, Chenlin Meng, Stefano Ermon

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Understanding Classifier Mistakes with Generative Models

Oct 05, 2020
Laëtitia Shao, Yang Song, Stefano Ermon

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* 17 pages, 10 figures. Submitted to ICLR2021 

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Using satellite imagery to understand and promote sustainable development

Sep 23, 2020
Marshall Burke, Anne Driscoll, David B. Lobell, Stefano Ermon

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Privacy Preserving Recalibration under Domain Shift

Aug 21, 2020
Rachel Luo, Shengjia Zhao, Jiaming Song, Jonathan Kuck, Stefano Ermon, Silvio Savarese

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HiPPO: Recurrent Memory with Optimal Polynomial Projections

Aug 17, 2020
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Re

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Multi-label Contrastive Predictive Coding

Jul 20, 2020
Jiaming Song, Stefano Ermon

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Efficient Learning of Generative Models via Finite-Difference Score Matching

Jul 07, 2020
Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu

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Individual Calibration with Randomized Forecasting

Jul 05, 2020
Shengjia Zhao, Tengyu Ma, Stefano Ermon

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Belief Propagation Neural Networks

Jul 01, 2020
Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon

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Unsupervised Calibration under Covariate Shift

Jun 29, 2020
Anusri Pampari, Stefano Ermon

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* Submitted to Conference on Uncertainty in Artificial Intelligence (UAI 2020) 

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Predicting Livelihood Indicators from Crowdsourced Street Level Images

Jun 27, 2020
Jihyeon Janel Lee, Dylan Grosz, Sicheng Zeng, Burak Uzkent, Marshall Burke, David Lobell, Stefano Ermon

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Experience Replay with Likelihood-free Importance Weights

Jun 23, 2020
Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon

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A Framework for Sample Efficient Interval Estimation with Control Variates

Jun 18, 2020
Shengjia Zhao, Christopher Yeh, Stefano Ermon

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Improved Techniques for Training Score-Based Generative Models

Jun 16, 2020
Yang Song, Stefano Ermon

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Efficient Poverty Mapping using Deep Reinforcement Learning

Jun 07, 2020
Kumar Ayush, Burak Uzkent, Marshall Burke, David Lobell, Stefano Ermon

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Evaluating the Disentanglement of Deep Generative Models through Manifold Topology

Jun 05, 2020
Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon

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MOPO: Model-based Offline Policy Optimization

May 27, 2020
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma

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* First two authors contributed equally. Last two authors advised equally 

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Farmland Parcel Delineation Using Spatio-temporal Convolutional Networks

Apr 20, 2020
Han Lin Aung, Burak Uzkent, Marshall Burke, David Lobell, Stefano Ermon

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Output Diversified Initialization for Adversarial Attacks

Mar 15, 2020
Yusuke Tashiro, Yang Song, Stefano Ermon

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Training Deep Energy-Based Models with f-Divergence Minimization

Mar 06, 2020
Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon

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Gaussianization Flows

Mar 04, 2020
Chenlin Meng, Yang Song, Jiaming Song, Stefano Ermon

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* AISTATS 2020 

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