David Meger
22 papers · 2017–2024 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (49) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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Keyword Pioneer
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Topic Evolution
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Keyword Champion
(2)
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Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
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Conference Pioneer
β
The Questioner
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Renaissance Researcher
(5)
ποΈ
Keyword Collector
(115)
Top co-authors
Research topics
Machine Learning
(13)
Reinforcement Learning
(11)
Methods
(10)
Artificial Intelligence
(8)
Deep Learning
(8)
Core AI
(8)
Learning Types Β· Machine Learning
(8)
Computer Vision
(5)
Analysis
(5)
Core Methods
(4)
Learning Types Β· Deep Learning
(4)
Optimization & Theory
(4)
Applications
(3)
Generation
(3)
Models
(3)
Keywords
continuous control
(4)
reinforcement learning
(4)
multimodal learning
(3)
3d reconstruction
(3)
policy gradient
(3)
value function
(3)
tactile sensing
(3)
deep reinforcement learning
(2)
3d object reconstruction
(2)
value function approximation
(2)
epistemic uncertainty
(2)
mesh reconstruction
(2)
transfer learning
(1)
robotic manipulation
(1)
imitation learning
(1)
image generation
(1)
continual learning
(1)
offline reinforcement learning
(1)
uncertainty quantification
(1)
state abstraction
(1)
Papers
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
NeurIPS 2024
Parseval Regularization for Continual Reinforcement Learning
NeurIPS 2024
Policy Gradient Methods in the Presence of Symmetries and State Abstractions
JMLR 2024
Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models
UAI 2024
For SALE: State-Action Representation Learning for Deep Reinforcement Learning
NeurIPS 2023
Hypernetworks for Zero-Shot Transfer in Reinforcement Learning
AAAI 2023
Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling
AAAI 2023
Continuous MDP Homomorphisms and Homomorphic Policy Gradient
NeurIPS 2022
Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning
ICML 2022
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error
ICML 2022
Active 3D Shape Reconstruction from Vision and Touch
NeurIPS 2021
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
ICML 2021
Learning Intuitive Physics with Multimodal Generative Models
AAAI 2021
Seeing Through Your Skin: Recognizing Objects With a Novel Visuotactile Sensor
WACV 2021
3D Shape Reconstruction from Vision and Touch
NeurIPS 2020
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
NeurIPS 2020
Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles
RSS 2020
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
ICML 2019
Off-Policy Deep Reinforcement Learning without Exploration
ICML 2019
Addressing Function Approximation Error in Actor-Critic Methods
ICML 2018
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation
NeurIPS 2018
Improved Adversarial Systems for 3D Object Generation and Reconstruction
CoRL 2017