Papers
Variational Inference for sparse network reconstruction from count data
Julien Chiquet, Stephane Robin, Mahendra Mariadassou
Variational Inference from Ranked Samples with Features
Yuan Guo, Jennifer Dy, Deniz Erdoğmuş et al.
Variational Inference MPC for Bayesian Model-based Reinforcement Learning
Masashi Okada, Tadahiro Taniguchi
Variational Inference of Penalized Regression with Submodular Functions
Koh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara
Variational Information Distillation for Knowledge Transfer
Sungsoo Ahn, Shell Xu Hu, Andreas Damianou et al.
Variational Information Planning for Sequential Decision Making
Jason Pacheco, John Fisher
Variational Laplace Autoencoders
Yookoon Park, Chris Kim, Gunhee Kim
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models
Yuge Shi, Siddharth N, Brooks Paige et al.
Variational Noise-Contrastive Estimation
Benjamin Rhodes, Michael U. Gutmann
Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems
Ethan N. Evans, Marcus A. Periera, George I. Boutselis et al.
Variational Pretraining for Semi-supervised Text Classification
Suchin Gururangan, Tam Dang, Dallas Card et al.
Variational Prototyping-Encoder: One-Shot Learning With Prototypical Images
Junsik Kim, Tae-Hyun Oh, Seokju Lee et al.
Variational Regret Bounds for Reinforcement Learning
Ronald Ortner, Pratik Gajane, Peter Auer
Variational Russian Roulette for Deep Bayesian Nonparametrics
Kai Xu, Akash Srivastava, Charles Sutton
Variational Semi-Supervised Aspect-Term Sentiment Analysis via Transformer
Xingyi Cheng, Weidi Xu, Taifeng Wang et al.
Variational Smoothing in Recurrent Neural Network Language Models
Lingpeng Kong, Gabor Melis, Wang Ling et al.
Variational Sparse Coding
Francesco Tonolini, Bjørn Sand Jensen, Roderick Murray-Smith
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
Variational Training for Large-Scale Noisy-OR Bayesian Networks
Geng Ji, Dehua Cheng, Huazhong Ning et al.
Variational Uncalibrated Photometric Stereo Under General Lighting
Bjoern Haefner, Zhenzhang Ye, Maolin Gao et al.
Variation between Different Discourse Types: Literate vs. Oral
Katrin Ortmann, Stefanie Dipper
Variation Generalized Feature Learning via Intra-view Variation Adaptation
Jiawei Li, Mang Ye, Andy Jinhua Ma et al.
VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research
Xin Wang, Jiawei Wu, Junkun Chen et al.
VC Classes are Adversarially Robustly Learnable, but Only Improperly
Omar Montasser, Steve Hanneke, Nathan Srebro