Papers
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such et al.
Improving Neural Program Synthesis with Inferred Execution Traces
Eui Chul Shin, Illia Polosukhin, Dawn Song
Improving Online Algorithms via ML Predictions
Manish Purohit, Zoya Svitkina, Ravi Kumar
Improving Simple Models with Confidence Profiles
Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss et al.
Incorporating Context into Language Encoding Models for fMRI
Shailee Jain, Alexander Huth
Inequity aversion improves cooperation in intertemporal social dilemmas
Edward Hughes, Joel Z. Leibo, Matthew Phillips et al.
Inexact trust-region algorithms on Riemannian manifolds
Hiroyuki Kasai, Bamdev Mishra
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing
Zehong Hu, Yitao Liang, Jie Zhang et al.
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
Inferring Latent Velocities from Weather Radar Data using Gaussian Processes
Rico Angell, Daniel R. Sheldon
Inferring Networks From Random Walk-Based Node Similarities
Jeremy Hoskins, Cameron Musco, Christopher Musco et al.
Infinite-Horizon Gaussian Processes
Arno Solin, James Hensman, Richard E Turner
Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer Interfaces
Boyla Mainsah, Dmitry Kalika, Leslie Collins et al.
Information Constraints on Auto-Encoding Variational Bayes
Romain Lopez, Jeffrey Regier, Michael I Jordan et al.
Information-theoretic Limits for Community Detection in Network Models
Chuyang Ke, Jean Honorio
Informative Features for Model Comparison
Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy et al.
Insights on representational similarity in neural networks with canonical correlation
Ari Morcos, Maithra Raghu, Samy Bengio
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
Amir Dezfouli, Richard Morris, Fabio T Ramos et al.
Interactive Structure Learning with Structural Query-by-Committee
Christopher Tosh, Sanjoy Dasgupta
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections
Xin Zhang, Armando Solar-Lezama, Rishabh Singh
IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis
Huaibo Huang, zhihang li, Ran He et al.
Invariant Representations without Adversarial Training
Daniel Moyer, Shuyang Gao, Rob Brekelmans et al.
Invertibility of Convolutional Generative Networks from Partial Measurements
Fangchang Ma, Ulas Ayaz, Sertac Karaman
Isolating Sources of Disentanglement in Variational Autoencoders
Ricky T. Q. Chen, Xuechen Li, Roger B Grosse et al.
Is Q-Learning Provably Efficient?
Chi Jin, Zeyuan Allen-Zhu, Sebastien Bubeck et al.