Research Talk Towards Efficient Generalization In Continual Rl Using Episodic Memory

Media Summary: Speaker: Mandana Samiei, PhD Student, McGill University and Mila (Quebec AI Institute) Reinforcement learning ( In classic supervised machine learning, a learning agent behaves as a passive observer: it receives examples from some external ... This is a demo video for the paper "DeGuV: Depth-Guided Visual Reinforcement Learning for

Research Talk Towards Efficient Generalization In Continual Rl Using Episodic Memory - Detailed Analysis & Overview

Speaker: Mandana Samiei, PhD Student, McGill University and Mila (Quebec AI Institute) Reinforcement learning ( In classic supervised machine learning, a learning agent behaves as a passive observer: it receives examples from some external ... This is a demo video for the paper "DeGuV: Depth-Guided Visual Reinforcement Learning for Speakers: Mingfei Sun, Researcher, Microsoft Speakers: Suha Kwak, Professor, POSTECH Chong Luo, Principal Researcher, Microsoft Amy Zhang is a final year PhD candidate at McGill University and the Mila Institute, co-supervised by Profs. Joelle Pineau and ...

Authors: Saha, Gobinda*; Roy, Kaushik Description: Artificial learning systems aspire to mimic human intelligence by Charan Ranganath, PhD, professor of psychology at the University of California, Davis, gave a LEARNMEM2023 plenary lecture ... Johanni Brea, Wulfram Gerstner, EPFL, Switzerland Birds of the crow family are well known for their complex cognition. [06-11-2020] This Friday 5.30pm CET, for the ContinualAI Reading Group, Jeremias Knoblauch presented the paper: Title: ...

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Research talk: Towards efficient generalization in continual RL using episodic memory

PAHF: Continual Agent Learning from Feedback

Towards Generalization and Efficiency in Reinforcement Learning

[DEMO] DeGuV: Depth Guided Visual Reinforcement Learning for Generalization

MetaGenRL: Improving Generalization in Meta Reinforcement Learning (ICLR 2020 Spotlight)

Latent Learning: Episodic Memory for LLMs

Panel: Generalization in reinforcement learning

Research talks: Generalization and adaptation

Amy Zhang Explores Generalization in RL by Exploiting Latent Structure and Bisimulation Metrics.

Saliency Guided Experience Packing for Replay in Continual Learning

Sparse Memory Finetuning for Continual LMs

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Research Talk Towards Efficient Generalization In Continual Rl Using Episodic Memory