Michelle A. Lee | DeepAI

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Featured Co-authors

Ruslan Salakhutdinov
194 publications
Dieter Fox
146 publications
Silvio Savarese
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Li Fei-Fei
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Animesh Garg
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Louis-Philippe Morency
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Fabio Ramos
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Yuke Zhu
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Paul Pu Liang
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Roberto Martín-Martín
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∙ 07/15/2021

MultiBench: Multiscale Benchmarks for Multimodal Representation Learning

Learning multimodal representations involves integrating information fro...

0 Paul Pu Liang, et al. ∙

∙ 05/18/2021

Differentiable Factor Graph Optimization for Learning Smoothers

A recent line of work has shown that end-to-end optimization of Bayesian...

0 Brent Yi, et al. ∙

∙ 01/07/2021

Interpreting Contact Interactions to Overcome Failure in Robot Assembly Tasks

A key challenge towards the goal of multi-part assembly tasks is finding...

0 Peter A. Zachares, et al. ∙

∙ 12/01/2020

Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors

Using sensor data from multiple modalities presents an opportunity to en...

0 Michelle A. Lee, et al. ∙

∙ 10/25/2020

Multimodal Sensor Fusion with Differentiable Filters

Leveraging multimodal information with recursive Bayesian filters improv...

0 Michelle A. Lee, et al. ∙

∙ 05/21/2020

Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning

Traditional robotic approaches rely on an accurate model of the environm...

33 Michelle A. Lee, et al. ∙

∙ 07/28/2019

Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks

Contact-rich manipulation tasks in unstructured environments often requi...

0 Michelle A. Lee, et al. ∙

∙ 06/20/2019

Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks

Reinforcement Learning (RL) of contact-rich manipulation tasks has yield...

2 Roberto Martín-Martín, et al. ∙

∙ 10/24/2018

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

Contact-rich manipulation tasks in unstructured environments often requi...

4 Michelle A. Lee, et al. ∙

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