Alex Lamb
18 papers · 2013–2025 · 7 venues · across top CS/AI venues
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Achievements
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Keyword Pioneer
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Dynamic Duo
(11)
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(7)
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Unstoppable Β· Bronze
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
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(88)
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Research topics
Machine Learning
(14)
Deep Learning
(11)
Architectures
(8)
Core Methods
(7)
Learning Types Β· Machine Learning
(7)
Artificial Intelligence
(6)
Reinforcement Learning
(5)
Learning Types Β· Deep Learning
(5)
Methods
(5)
Application Areas
(4)
Core AI
(4)
Techniques
(4)
Learning Paradigms
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Keywords
representation learning
(7)
attention mechanism
(4)
latent state
(3)
reinforcement learning
(3)
semi-supervised learning
(2)
recurrent neural network
(2)
visual observation
(1)
sentiment analysis
(1)
offline reinforcement learning
(1)
domain adaptation
(1)
image translation
(1)
information bottleneck
(1)
hierarchical planning
(1)
self-supervised learning
(1)
transfer learning
(1)
sample complexity
(1)
multimodal learning
(1)
variational inference
(1)
social media analysis
(1)
domain generalization
(1)
Papers
The Belief State Transformer
ICLR 2025
Towards Improving Exploration through Sibling Augmented GFlowNets
ICLR 2025
PcLast: Discovering Plannable Continuous Latent States
ICML 2024
Towards Principled Representation Learning from Videos for Reinforcement Learning
ICLR 2024
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness
AAAI 2023
Principled Offline RL in the Presence of Rich Exogenous Information
ICML 2023
Representation Learning in Deep RL via Discrete Information Bottleneck
AISTATS 2023
Coordination Among Neural Modules Through a Shared Global Workspace
ICLR 2022
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
ICLR 2021
GraphMix: Improved Training of GNNs for Semi-Supervised Learning
AAAI 2021
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
AISTATS 2021
Recurrent Independent Mechanisms
ICLR 2021
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
ICML 2020
SketchTransfer: A New Dataset for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks
WACV 2020
Interpolation Consistency Training for Semi-supervised Learning
IJCAI 2019
Manifold Mixup: Better Representations by Interpolating Hidden States
ICML 2019
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
ICML 2019
Separating Fact from Fear: Tracking Flu Infections on Twitter
NAACL 2013