Alvaro Velasquez

Orcid: 0000-0001-6757-105X

According to our database1, Alvaro Velasquez authored at least 111 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence.
IEEE Trans. Artif. Intell., August, 2024

Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences.
IEEE Trans. Artif. Intell., July, 2024

Arc-dependent networks: theoretical insights and a computational study.
Ann. Oper. Res., July, 2024

Controller synthesis for linear temporal logic and steady-state specifications.
Auton. Agents Multi Agent Syst., June, 2024

Neurosymbolic Reinforcement Learning and Planning: A Survey.
IEEE Trans. Artif. Intell., May, 2024

Farkas Bounds on Horn Constraint Systems.
Theory Comput. Syst., April, 2024

Priority-based bin packing with subset constraints.
Discret. Appl. Math., January, 2024

Robust Average-Reward Reinforcement Learning.
J. Artif. Intell. Res., 2024

Criticality and Safety Margins for Reinforcement Learning.
CoRR, 2024

On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks.
CoRR, 2024

Bioinformatics Retrieval Augmentation Data (BRAD) Digital Assistant.
CoRR, 2024

A Survey on Symbolic Knowledge Distillation of Large Language Models.
CoRR, 2024

LLMs as Probabilistic Minimally Adequate Teachers for DFA Learning.
CoRR, 2024

Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm.
CoRR, 2024

Combining AI Control Systems and Human Decision Support via Robustness and Criticality.
CoRR, 2024

Dataless Quadratic Neural Networks for the Maximum Independent Set Problem.
CoRR, 2024

Bayesian Inverse Reinforcement Learning for Non-Markovian Rewards.
CoRR, 2024

Hyperdimensional Quantum Factorization.
CoRR, 2024

Neuro-symbolic Generative AI Assistant for System Design.
Proceedings of the 22nd ACM-IEEE International Symposium on Formal Methods and Models for System Design, 2024

A Differential Approach for Several NP-hard Optimization Problems.
Proceedings of the Artificial Intelligence and Image Analysis, 2024

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents.
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments.
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

Solving Mystery Planning Problems Using Category Theory, Functors, and Large Language Models.
Proceedings of the International Conference on Assured Autonomy, 2024

On the Design of Novel Attention Mechanism for Enhanced Efficiency of Transformers.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning.
Proceedings of the IEEE Conference on Cognitive and Computational Aspects of Situation Management, 2024

LgTS: Dynamic Task Sampling using LLM-generated Sub-Goals for Reinforcement Learning Agents.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Assume-Guarantee Reinforcement Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Artifact for "Assume-Guarantee Reinforcement Learning".
Dataset, December, 2023

Reachability problems in interval-constrained and cardinality-constrained graphs.
Discret. Math. Algorithms Appl., May, 2023

Reachability in choice networks.
Discret. Optim., May, 2023

Optimal Deterministic Controller Synthesis from Steady-State Distributions.
J. Autom. Reason., March, 2023

Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning.
CoRR, 2023

Byzantine-Resilient Decentralized Multi-Armed Bandits.
CoRR, 2023

Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving.
CoRR, 2023

Neural Stochastic Differential Equations for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions.
CoRR, 2023

Safety Margins for Reinforcement Learning.
CoRR, 2023

On the Robustness of AlphaFold: A COVID-19 Case Study.
CoRR, 2023

Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving.
Proceedings of the IEEE Military Communications Conference, 2023

Neural SDEs for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions.
Proceedings of the IEEE Military Communications Conference, 2023

A Non-Targeted Attack Approach for the Coarse Misclassification Problem.
Proceedings of the International Joint Conference on Neural Networks, 2023

Model-Free Robust Average-Reward Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection.
Proceedings of the IEEE International Conference on Data Mining, 2023

Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting.
Proceedings of the IEEE International Conference on Assured Autonomy, 2023

NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

The Octatope Abstract Domain for Verification of Neural Networks.
Proceedings of the Formal Methods - 25th International Symposium, 2023

Differentiable Discrete Optimization Using Dataless Neural Networks.
Proceedings of the Combinatorial Optimization and Applications, 2023

A Resilient Distributed Algorithm for Solving Linear Equations.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

LTL-Based Non-Markovian Inverse Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Resilient Distributed Optimization<sup>*</sup>.
Proceedings of the American Control Conference, 2023

Automaton-Guided Curriculum Generation for Reinforcement Learning Agents.
Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling, 2023

Robust Average-Reward Markov Decision Processes.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
On the complexity of and solutions to the minimum stopping and trapping set problems.
Theor. Comput. Sci., 2022

A differentiable approach to the maximum independent set problem using dataless neural networks.
Neural Networks, 2022

Resilient Distributed Optimization.
CoRR, 2022

A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks.
CoRR, 2022

Data-Driven Robust Multi-Agent Reinforcement Learning.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

The Minimum Value State Problem in Actor-Critic Networks.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

A Differentiable Approach to the Maximum Independent Set Problem Using Graph-Based Neural Network Structures.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Reinforced Contrastive Graph Neural Networks (RCGNN) for Anomaly Detection.
Proceedings of the IEEE International Performance, 2022

Exploring Adversarial Attacks on Neural Networks: An Explainable Approach.
Proceedings of the IEEE International Performance, 2022

ExplainIt!: A Tool for Computing Robust Attributions of DNNs.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Synthesis of Adversarial Samples in Two-Stage Classifiers.
Proceedings of the IEEE International Conference on Acoustics, 2022

Analyzing the Reachability Problem in Choice Networks.
Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2022

On the Approximability of Path and Cycle Problems in Arc-Dependent Networks.
Proceedings of the Algorithms and Discrete Applied Mathematics, 2022

Controller Synthesis for Omega-Regular and Steady-State Specifications.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Translating Omega-Regular Specifications to Average Objectives for Model-Free Reinforcement Learning.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Resilient Constrained Consensus over Complete Graphs via Feasibility Redundancy.
Proceedings of the American Control Conference, 2022

New Results in Priority-Based Bin Packing.
Proceedings of the Algorithmic Aspects of Cloud Computing - 7th International Symposium, 2022

Multi-Agent Tree Search with Dynamic Reward Shaping.
Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

Active Grammatical Inference for Non-Markovian Planning.
Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning.
Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

On the Coarse Robustness of Classifiers.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Steady-State Planning in Expected Reward Multichain MDPs.
J. Artif. Intell. Res., 2021

Protein Folding Neural Networks Are Not Robust.
CoRR, 2021

Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks.
CoRR, 2021

Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes.
CoRR, 2021

Adversarial Perturbation Attacks on Nested Dichotomies Classification Systems.
Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Automated Synthesis of Quantum Circuits Using Symbolic Abstractions and Decision Procedures.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

On Smoother Attributions using Neural Stochastic Differential Equations.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

On the Copy Complexity of Width 3 Horn Constraint Systems.
Proceedings of the Frontiers of Combining Systems - 13th International Symposium, 2021

Consensus-Based Value Iteration for Multiagent Cooperative Control.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Algorithmic Analysis of Priority-Based Bin Packing.
Proceedings of the Algorithms and Discrete Applied Mathematics, 2021

Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Verifiable Planning in Expected Reward Multichain MDPs.
CoRR, 2020

Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions.
CoRR, 2020

An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks.
CoRR, 2020

Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture.
CoRR, 2020

The Utility of Feature Reuse: Transfer Learning in Data-Starved Regimes.
CoRR, 2020

FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints.
Proceedings of the 2020 USENIX Conference on Operational Machine Learning, 2020

Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

Steady-State Policy Synthesis in Multichain Markov Decision Processes.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

Verification-Guided Tree Search.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Spatially Efficient In-Memory Addition Through Destructive and Non-Destructive Operations.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

Steady-State Policy Synthesis for Verifiable Control.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

On the Susceptibility of Deep Neural Networks to Natural Perturbations.
Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 2019

2018
Brief Announcement: Parallel Transitive Closure Within 3D Crosspoint Memory.
Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures, 2018

Finding Minimum Stopping and Trapping Sets: An Integer Linear Programming Approach.
Proceedings of the Combinatorial Optimization - 5th International Symposium, 2018

3D Crosspoint Memory as a Parallel Architecture for Computing Network Reachability.
Proceedings of the 36th IEEE International Conference on Computer Design, 2018

In-memory computing using paths-based logic and heterogeneous components.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

Minimization of Testing Costs in Capacity-Constrained Database Migration.
Proceedings of the Algorithmic Aspects of Cloud Computing - 4th International Symposium, 2018

2017
Computation of Boolean matrix chain products in 3D ReRAM.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

2016
The cardinality-constrained paths problem: Multicast data routing in heterogeneous communication networks.
Proceedings of the 15th IEEE International Symposium on Network Computing and Applications, 2016

Parallel boolean matrix multiplication in linear time using rectifying memristors.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Flow-based computing on nanoscale crossbars: Design and implementation of full adders.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

2015
Automated synthesis of crossbars for nanoscale computing using formal methods.
Proceedings of the 2015 IEEE/ACM International Symposium on Nanoscale Architectures, 2015

Fault-tolerant in-memory crossbar computing using quantified constraint solving.
Proceedings of the 33rd IEEE International Conference on Computer Design, 2015

2014
Parallel computing using memristive crossbar networks: Nullifying the processor-memory bottleneck.
Proceedings of the 9th International Design and Test Symposium, 2014

Putting humpty-dumpty together: Mining causal mechanistic biochemical models from big data.
Proceedings of the IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences, 2014


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