Philip Bachman
15 papers · 2014–2023 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+6 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (40) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π§
Keyword Pioneer
π
Triple Crown
ποΈ
Keyword Collector
(63)
π
Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(12)
Learning Types Β· Machine Learning
(11)
Core Methods
(8)
Artificial Intelligence
(6)
Deep Learning
(6)
Learning Paradigms
(4)
Learning Types Β· Deep Learning
(4)
Core AI
(3)
Models
(3)
Reinforcement Learning
(2)
Architectures
(2)
Optimization & Theory
(2)
Computer Vision
(1)
Natural Language Processing
(1)
Application Areas
(1)
Keywords
representation learning
(6)
generative model
(3)
variational inference
(2)
reinforcement learning
(2)
mutual information
(2)
contrastive learning
(2)
continual learning
(1)
function approximation
(1)
deep reinforcement learning
(1)
sentiment analysis
(1)
image generation
(1)
model robustness
(1)
sequential decision making
(1)
self-supervised learning
(1)
image reconstruction
(1)
data augmentation
(1)
image translation
(1)
markov decision process
(1)
semi-supervised learning
(1)
active learning
(1)
Papers
Ignorance is Bliss: Robust Control via Information Gating
NeurIPS 2023
Data-Efficient Reinforcement Learning with Self-Predictive Representations
ICLR 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning
ICML 2021
Pretraining Representations for Data-Efficient Reinforcement Learning
NeurIPS 2021
Deep Reinforcement and InfoMax Learning
NeurIPS 2020
Learning Representations by Maximizing Mutual Information Across Views
NeurIPS 2019
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
ICML 2018
Learning Algorithms for Active Learning
ICML 2017
An Architecture for Deep, Hierarchical Generative Models
NeurIPS 2016
A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data
ACL 2016
Natural Language Comprehension with the EpiReader
EMNLP 2016
Data Generation as Sequential Decision Making
NeurIPS 2015
Variational Generative Stochastic Networks with Collaborative Shaping
ICML 2015
Learning with Pseudo-Ensembles
NeurIPS 2014
Sample-based approximate regularization
ICML 2014