Ankit Anand | DeepAI

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∙ 08/29/2023

Policy composition in reinforcement learning via multi-objective policy optimization

We enable reinforcement learning agents to learn successful behavior pol...

0 Shruti Mishra, et al. ∙

∙ 03/31/2023

Accelerating exploration and representation learning with offline pre-training

Sequential decision-making agents struggle with long horizon tasks, sinc...

0 Bogdan Mazoure, et al. ∙

∙ 12/20/2021

Proving Theorems using Incremental Learning and Hindsight Experience Replay

Traditional automated theorem provers for first-order logic depend on sp...

0 Eser Aygün, et al. ∙

∙ 03/05/2021

Training a First-Order Theorem Prover from Synthetic Data

A major challenge in applying machine learning to automated theorem prov...

0 Vlad Firoiu, et al. ∙

∙ 10/04/2020

Learning Compositional Structures for Deep Learning: Why Routing-by-agreement is Necessary

A formal description of the compositionality of neural networks is assoc...

0 Sai Raam Venkatraman, et al. ∙

∙ 06/19/2020

Learning to Prove from Synthetic Theorems

A major challenge in applying machine learning to automated theorem prov...

0 Eser Aygün, et al. ∙

∙ 05/16/2020

AccentDB: A Database of Non-Native English Accents to Assist Neural Speech Recognition

Modern Automatic Speech Recognition (ASR) technology has evolved to iden...

0 Afroz Ahamad, et al. ∙

∙ 07/02/2018

Block-Value Symmetries in Probabilistic Graphical Models

Several lifted inference algorithms for probabilistic graphical models f...

0 Gagan Madan, et al. ∙

∙ 07/27/2017

Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models

Lifted inference algorithms commonly exploit symmetries in a probabilist...

0 Ankit Anand, et al. ∙

∙ 07/22/2017

Coarse-to-Fine Lifted MAP Inference in Computer Vision

There is a vast body of theoretical research on lifted inference in prob...

0 Haroun Habeeb, et al. ∙

∙ 06/30/2016

Contextual Symmetries in Probabilistic Graphical Models

An important approach for efficient inference in probabilistic graphical...

0 Ankit Anand, et al. ∙

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