Alvaro Velasquez | DeepAI

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∙ 07/25/2023

Safety Margins for Reinforcement Learning

Any autonomous controller will be unsafe in some situations. The ability...

0 Alexander Grushin, et al. ∙

∙ 05/17/2023

Model-Free Robust Average-Reward Reinforcement Learning

Robust Markov decision processes (MDPs) address the challenge of model u...

0 Yue Wang, et al. ∙

∙ 04/11/2023

Automaton-Guided Curriculum Generation for Reinforcement Learning Agents

Despite advances in Reinforcement Learning, many sequential decision mak...

0 Yash Shukla, et al. ∙

∙ 03/09/2023

NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks

Deep Learning (DL) and Deep Neural Networks (DNNs) are widely used in va...

7 Wenkai Tan, et al. ∙

∙ 03/08/2023

Exploring Adversarial Attacks on Neural Networks: An Explainable Approach

Deep Learning (DL) is being applied in various domains, especially in sa...

0 Justus Renkhoff, et al. ∙

∙ 03/07/2023

SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection

Detecting human-object interactions (HOIs) is a challenging problem in c...

0 Lijing Zhu, et al. ∙

∙ 01/10/2023

On the Robustness of AlphaFold: A COVID-19 Case Study

Protein folding neural networks (PFNNs) such as AlphaFold predict remark...

0 Ismail Alkhouri, et al. ∙

∙ 01/02/2023

Robust Average-Reward Markov Decision Processes

In robust Markov decision processes (MDPs), the uncertainty in the trans...

0 Yue Wang, et al. ∙

∙ 03/15/2022

A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks

The success of machine learning solutions for reasoning about discrete s...

0 Ismail R. Alkhouri, et al. ∙

∙ 09/09/2021

Protein Folding Neural Networks Are Not Robust

Deep neural networks such as AlphaFold and RoseTTAFold predict remarkabl...

0 Sumit Kumar Jha, et al. ∙

∙ 09/01/2021

Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks

Convolutional neural networks (CNN) are now being widely used for classi...

17 Edward Verenich, et al. ∙

∙ 08/05/2021

BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples

The design of additive imperceptible perturbations to the inputs of deep...

5 Ismail Alkhouri, et al. ∙

∙ 07/09/2021

Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes

The success of reinforcement learning in typical settings is, in part, p...

0 Alvaro Velasquez, et al. ∙

∙ 06/05/2021

Controller Synthesis for Omega-Regular and Steady-State Specifications

Given a Markov decision process (MDP) and a linear-time (ω-regular or LT...

0 Alvaro Velasquez, et al. ∙

∙ 12/03/2020

Verifiable Planning in Expected Reward Multichain MDPs

The planning domain has experienced increased interest in the formal syn...

0 George K. Atia, et al. ∙

∙ 11/11/2020

Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions

Complementary metal oxide semiconductor (CMOS) devices display volatile ...

10 Wesley H. Brigner, et al. ∙

∙ 09/17/2020

An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks

Deep neural networks have been shown to be vulnerable to membership infe...

8 Sumit Kumar Jha, et al. ∙

∙ 08/06/2020

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia

Trust in predictions made by machine learning models is increased if the...

0 Edward Verenich, et al. ∙

∙ 03/24/2020

Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture

We propose a hardware learning rule for unsupervised clustering within a...

0 Alvaro Velasquez, et al. ∙

∙ 03/04/2020

Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning

Machine learning implements backpropagation via abundant training sample...

7 Christopher H. Bennett, et al. ∙

∙ 02/29/2020

FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints

The integration of artificial intelligence capabilities into modern soft...

0 Edward Verenich, et al. ∙

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