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Anytime Sampling for Autoregressive Models via Ordered Autoencoding


Feb 23, 2021
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon

* Accepted by ICLR 2021 

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Localized Calibration: Metrics and Recalibration


Feb 22, 2021
Rachel Luo, Aadyot Bhatnagar, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai, Shengjia Zhao, Stefano Ermon


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Neural Network Compression for Noisy Storage Devices


Feb 15, 2021
Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi

* 19 pages, 9 figures 

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Negative Data Augmentation


Feb 09, 2021
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon

* Accepted at ICLR 2021 

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Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients


Jan 02, 2021
Chris Cundy, Stefano Ermon

* 8 pages; figure/table formatting fixed 

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PiRank: Learning To Rank via Differentiable Sorting


Dec 12, 2020
Robin Swezey, Aditya Grover, Bruno Charron, Stefano Ermon


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Efficient Conditional Pre-training for Transfer Learning


Dec 10, 2020
Shuvam Chakraborty, Burak Uzkent, Kumar Ayush, Kumar Tanmay, Evan Sheehan, Stefano Ermon


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Geography-Aware Self-Supervised Learning


Dec 02, 2020
Kumar Ayush, Burak Uzkent, Chenlin Meng, Kumar Tanmay, Marshall Burke, David Lobell, Stefano Ermon


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Score-Based Generative Modeling through Stochastic Differential Equations


Nov 26, 2020
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole


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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

* NeurIPS 2020 

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Probabilistic Circuits for Variational Inference in Discrete Graphical Models


Oct 22, 2020
Andy Shih, Stefano Ermon

* 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

* 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

* 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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