Papers
Using Embeddings to Correct for Unobserved Confounding in Networks
Victor Veitch, Yixin Wang, David Blei
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
Dan Hendrycks, Mantas Mazeika, Saurav Kadavath et al.
Using Statistics to Automate Stochastic Optimization
Hunter Lang, Lin Xiao, Pengchuan Zhang
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
Mathias Perslev, Michael Jensen, Sune Darkner et al.
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm
Amir-massoud Farahmand
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
Chao Qu, Shie Mannor, Huan Xu et al.
Variance Reduced Policy Evaluation with Smooth Function Approximation
Hoi-To Wai, Mingyi Hong, Zhuoran Yang et al.
Variance Reduction for Matrix Games
Yair Carmon, Yujia Jin, Aaron Sidford et al.
Variance Reduction in Bipartite Experiments through Correlation Clustering
Jean Pouget-Abadie, Kevin Aydin, Warren Schudy et al.
Variational Bayesian Decision-making for Continuous Utilities
Tomasz Kuśmierczyk, Joseph Sakaya, Arto Klami
Variational Bayesian Optimal Experimental Design
Adam Foster, Martin Jankowiak, Elias Bingham et al.
Variational Bayes under Model Misspecification
Yixin Wang, David Blei
Variational Denoising Network: Toward Blind Noise Modeling and Removal
Zongsheng Yue, Hongwei Yong, Qian Zhao et al.
Variational Graph Recurrent Neural Networks
Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna Narayanan et al.
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models
Yuge Shi, Siddharth N, Brooks Paige et al.
Variational Structured Semantic Inference for Diverse Image Captioning
Fuhai Chen, Rongrong Ji, Jiayi Ji et al.
Variational Temporal Abstraction
Taesup Kim, Sungjin Ahn, Yoshua Bengio
Verified Uncertainty Calibration
Ananya Kumar, Percy Liang, Tengyu Ma
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
Fan-Yun Sun, Meng Qu, Jordan Hoffmann et al.
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Jiasen Lu, Dhruv Batra, Devi Parikh et al.
VIREL: A Variational Inference Framework for Reinforcement Learning
Matthew Fellows, Anuj Mahajan, Tim G. J. Rudner et al.
Visual Concept-Metaconcept Learning
Chi Han, Jiayuan Mao, Chuang Gan et al.
Visualizing and Measuring the Geometry of BERT
Emily Reif, Ann Yuan, Martin Wattenberg et al.
Visualizing the PHATE of Neural Networks
Scott Gigante, Adam S Charles, Smita Krishnaswamy et al.