Akshat Kumar | DeepAI

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∙ 04/06/2023

Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects

In safe MDP planning, a cost function based on the current state and act...

5 Siow Meng Low, et al. ∙

∙ 12/01/2022

Shining light on data: Geometric data analysis through quantum dynamics

Experimental sciences have come to depend heavily on our ability to orga...

0 Akshat Kumar, et al. ∙

∙ 07/13/2022

DeepTIMe: Deep Time-Index Meta-Learning for Non-Stationary Time-Series Forecasting

Deep learning has been actively applied to time-series forecasting, lead...

1 Gerald Woo, et al. ∙

∙ 05/02/2022

Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies

Modern software systems rely on mining insights from business sensitive ...

0 Mikhail Kazdagli, et al. ∙

∙ 03/23/2022

Sample-efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs

Recent advances in deep learning have enabled optimization of deep react...

0 Siow Meng Low, et al. ∙

∙ 02/12/2022

InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools

Existing approaches for embedding unobtrusive tags inside 3D objects req...

0 Mustafa Doga Dogan, et al. ∙

∙ 02/03/2022

CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting

Deep learning has been actively studied for time series forecasting, and...

0 Gerald Woo, et al. ∙

∙ 02/03/2022

ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Transformers have been actively studied for time-series forecasting in r...

0 Gerald Woo, et al. ∙

∙ 12/20/2021

Manifold learning via quantum dynamics

We introduce an algorithm for computing geodesics on sampled manifolds t...

0 Akshat Kumar, et al. ∙

∙ 11/09/2020

Combining Propositional Logic Based Decision Diagrams with Decision Making in Urban Systems

Solving multiagent problems can be an uphill task due to uncertainty in ...

0 Jiajing Ling, et al. ∙

∙ 12/03/2018

Resource Constrained Deep Reinforcement Learning

In urban environments, supply resources have to be constantly matched to...

0 Abhinav Bhatia, et al. ∙

∙ 04/09/2018

Policy Gradient With Value Function Approximation For Collective Multiagent Planning

Decentralized (PO)MDPs provide an expressive framework for sequential de...

0 Duc Thien Nguyen, et al. ∙

∙ 12/01/2016

Robust Optimization for Tree-Structured Stochastic Network Design

Stochastic network design is a general framework for optimizing network ...

0 Xiaojian Wu, et al. ∙

∙ 03/15/2012

Anytime Planning for Decentralized POMDPs using Expectation Maximization

Decentralized POMDPs provide an expressive framework for multi-agent seq...

0 Akshat Kumar, et al. ∙

∙ 02/14/2012

Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation

Computing maximum a posteriori (MAP) estimation in graphical models is a...

0 Akshat Kumar, et al. ∙

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