Entropic Causal Inference: Identifiability and Finite Sample Results Spencer Compton
- Spencer Compton
- Murat Kocaoglu
- et al.
- 2020
- NeurIPS 2020
Conference paper
Publications
81 results at NeurIPS 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
- Ziv Goldfeld
- Kristjan Greenewald
- et al.
- 2020
- NeurIPS 2020
Conference paperTraining Stronger Baselines for Learning to Optimize
- Tianlong Chen
- Weiyi Zhang
- et al.
- 2020
- NeurIPS 2020
Conference paperLog-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
- Ben Usman
- Avneesh Sud
- et al.
- 2020
- NeurIPS 2020
Conference paperHeavy-tailed Representations, Text Polarity Classification & Data Augmentation
- Hamid Jalalzai
- Pierre Colombo
- et al.
- 2020
- NeurIPS 2020
Conference paperRevisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
- Minh Hoang
- Trong Nghia Hoang
- et al.
- 2020
- NeurIPS 2020
Conference paperModel Agnostic Learning of Multilevel Explanations
- Karthikeyan Natesan Ramamurthy
- Bhanu Vinzamuri
- et al.
- 2020
- NeurIPS 2020
Conference paperPrivate Identity Testing for High-Dimensional Distributions
- Clément L. Canonne
- Gautam Kamath
- et al.
- 2020
- NeurIPS 2020
Conference paperFinding the Homology of Decision Boundaries with Active Learning
- Weizhi Li
- Gautam Dasarathy
- et al.
- 2020
- NeurIPS 2020
Conference paperDAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
- Dennis Wei
- Tian Gao
- et al.
- 2020
- NeurIPS 2020
Conference paper