Alvaro Velasquez

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 118

Top Venues

Publications

Prathyush Poduval, Zhuowen Zou, Alvaro Velasquez, Mohsen Imani
Hyperdimensional Quantum Factorization. CoRR (2024)
Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Alvaro Velasquez
Assume-Guarantee Reinforcement Learning. AAAI (2024)
Alvaro Velasquez, Ismail Alkhouri, Andre Beckus, Ashutosh Trivedi, George K. Atia
Controller synthesis for linear temporal logic and steady-state specifications. Auton. Agents Multi Agent Syst. 38 (1) (2024)
Alvaro Velasquez, Piotr Wojciechowski, K. Subramani, Matthew D. Williamson
Arc-dependent networks: theoretical insights and a computational study. Ann. Oper. Res. 338 (2) (2024)
Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov
Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. ICAPS (2024)
Sangram Kishor Jena, K. Subramani, Alvaro Velasquez
A Differential Approach for Several NP-hard Optimization Problems. ISAIM (2024)
Noah Topper, Alvaro Velasquez, George K. Atia
Bayesian Inverse Reinforcement Learning for Non-Markovian Rewards. CoRR (2024)
Justus Renkhoff, Ke Feng, Marc Meier-Doernberg, Alvaro Velasquez, Houbing Herbert Song
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence. CoRR (2024)
Ismail R. Alkhouri, Sumit Kumar Jha, Andre Beckus, George K. Atia, Susmit Jha, Rickard Ewetz, Alvaro Velasquez
Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences. IEEE Trans. Artif. Intell. 5 (7) (2024)
Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou
Robust Average-Reward Reinforcement Learning. J. Artif. Intell. Res. 80 (2024)
K. Subramani, Piotr Wojciechowki, Alvaro Velasquez
Farkas Bounds on Horn Constraint Systems. Theory Comput. Syst. 68 (2) (2024)
Calvin Nau, Prashant Sankaran, Moises Sudit, Payam Khazaelpour, Katie McConky, Alvaro Velasquez, Liise Kayler
An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning. CogSIMA (2024)
Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, Jivko Sinapov
LgTS: Dynamic Task Sampling using LLM-generated Sub-Goals for Reinforcement Learning Agents. AAMAS (2024)
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li, Cunxi Yu, Jia Liu, Rongrong Wang, Alvaro Velasquez
Dataless Quadratic Neural Networks for the Maximum Independent Set Problem. CoRR (2024)
Kamal Acharya, Waleed Raza, Carlos M. J. M. Dourado Júnior, Alvaro Velasquez, Houbing Herbert Song
Neurosymbolic Reinforcement Learning and Planning: A Survey. IEEE Trans. Artif. Intell. 5 (5) (2024)
Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov
Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. CoRR (2024)
Walt Woods, Alexander Grushin, Simon Khan, Alvaro Velasquez
Combining AI Control Systems and Human Decision Support via Robustness and Criticality. CoRR (2024)
Piotr Wojciechowski, K. Subramani, Alvaro Velasquez, Bugra Çaskurlu
Priority-based bin packing with subset constraints. Discret. Appl. Math. 342 (2024)
Justus Renkhoff, Ke Feng, Marc Meier-Doernberg, Alvaro Velasquez, Houbing Herbert Song
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence. IEEE Trans. Artif. Intell. 5 (8) (2024)
Abhinav Rajvanshi, Karan Sikka, Xiao Lin, Bhoram Lee, Han-Pang Chiu, Alvaro Velasquez
SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments. ICAPS (2024)
Kamal Acharya, Waleed Raza, Carlos M. J. M. Dourado Júnior, Alvaro Velasquez, Houbing Song
Neurosymbolic Reinforcement Learning and Planning: A Survey. CoRR (2023)
Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu
Byzantine-Resilient Decentralized Multi-Armed Bandits. CoRR (2023)
Yash Shukla, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents. CoRR (2023)
Suraj Singireddy, Andre Beckus, George K. Atia, Sumit Kumar Jha, Alvaro Velasquez
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning. CoRR (2023)
Alvaro Velasquez, K. Subramani, Piotr Wojciechowski
Reachability problems in interval-constrained and cardinality-constrained graphs. Discret. Math. Algorithms Appl. 15 (4) (2023)
Mohammad Afzal, Sankalp Gambhir, Ashutosh Gupta, Krishna S, Ashutosh Trivedi, Alvaro Velasquez
LTL-Based Non-Markovian Inverse Reinforcement Learning. AAMAS (2023)
Wenkai Tan, Justus Renkhoff, Alvaro Velasquez, Ziyu Wang, Lusi Li, Jian Wang, Shuteng Niu, Fan Yang, Yongxin Liu, Houbing Song
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks. CoRR (2023)
Sangram K. Jena, K. Subramani, Alvaro Velasquez
Differentiable Discrete Optimization Using Dataless Neural Networks. COCOA (2) (2023)
Sumit Kumar Jha, Susmit Jha, Rickard Ewetz, Alvaro Velasquez
Neural Stochastic Differential Equations for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. CoRR (2023)
Lijing Zhu, Qizhen Lan, Alvaro Velasquez, Houbing Song, Acharya Kamal, Qing Tian, Shuteng Niu
SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection. ICDM (Workshops) (2023)
Jingxuan Zhu, Alvaro Velasquez, Ji Liu
A Resilient Distributed Algorithm for Solving Linear Equations. CDC (2023)
Lijing Zhu, Qizhen Lan, Alvaro Velasquez, Houbing Song, Acharya Kamal, Qing Tian, Shuteng Niu
SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection. CoRR (2023)
Sumit Kumar Jha, Susmit Jha, Rickard Ewetz, Alvaro Velasquez
Neural SDEs for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. MILCOM (2023)
Ismail Alkhouri, Sumit Kumar Jha, Andre Beckus, George Atia, Alvaro Velasquez, Rickard Ewetz, Arvind Ramanathan, Susmit Jha
On the Robustness of AlphaFold: A COVID-19 Case Study. CoRR (2023)
Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia
A Non-Targeted Attack Approach for the Coarse Misclassification Problem. IJCNN (2023)
Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou
Model-Free Robust Average-Reward Reinforcement Learning. CoRR (2023)
Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema
Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving. MILCOM (2023)
Wenkai Tan, Justus Renkhoff, Alvaro Velasquez, Ziyu Wang, Lusi Li, Jian Wang, Shuteng Niu, Fan Yang, Yongxin Liu, Houbing Song
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks. FUZZ (2023)
Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu
. ACC (2023)
Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, Jivko Sinapov
LgTS: Dynamic Task Sampling using LLM-generated sub-goals for Reinforcement Learning Agents. CoRR (2023)
Piotr Wojciechowski, K. Subramani, Alvaro Velasquez
Reachability in choice networks. Discret. Optim. 48 (Part 1) (2023)
Yash Shukla, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents. ICAPS (2023)
Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou
Robust Average-Reward Markov Decision Processes. CoRR (2023)
Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou
Robust Average-Reward Markov Decision Processes. AAAI (2023)
Justus Renkhoff, Wenkai Tan, Alvaro Velasquez, William Yichen Wang, Yongxin Liu, Jian Wang, Shuteng Niu, Lejla Begic Fazlic, Guido Dartmann, Houbing Song
Exploring Adversarial Attacks on Neural Networks: An Explainable Approach. CoRR (2023)
Jingxuan Zhu, Alvaro Velasquez, Ji Liu
A Resilient Distributed Algorithm for Solving Linear Equations. CoRR (2023)
Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou
Model-Free Robust Average-Reward Reinforcement Learning. ICML (2023)
Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema
Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving. CoRR (2023)
Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Alvaro Velasquez
Assume-Guarantee Reinforcement Learning. CoRR (2023)
Alexander Grushin, Walt Woods, Alvaro Velasquez, Simon Khan
Safety Margins for Reinforcement Learning. CoRR (2023)
Susmit Jha, Sumit Kumar Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Sandeep Neema
Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting. ICAA (2023)
Abhinav Rajvanshi, Karan Sikka, Xiao Lin, Bhoram Lee, Han-Pang Chiu, Alvaro Velasquez
SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments. CoRR (2023)
Alvaro Velasquez, Ismail Alkhouri, K. Subramani, Piotr Wojciechowski, George K. Atia
Optimal Deterministic Controller Synthesis from Steady-State Distributions. J. Autom. Reason. 67 (1) (2023)
Stanley Bak, Taylor Dohmen, K. Subramani, Ashutosh Trivedi, Alvaro Velasquez, Piotr Wojciechowski
The Octatope Abstract Domain for Verification of Neural Networks. FM (2023)
Piotr J. Wojciechowski, K. Subramani, Alvaro Velasquez, Matthew D. Williamson
On the Approximability of Path and Cycle Problems in Arc-Dependent Networks. CALDAM (2022)
Piotr Wojciechowski, K. Subramani, Alvaro Velasquez
Analyzing the Reachability Problem in Choice Networks. CPAIOR (2022)
Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu
Resilient Distributed Optimization. CoRR (2022)
Taylor Dohmen, Noah Topper, George K. Atia, Andre Beckus, Ashutosh Trivedi, Alvaro Velasquez
Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning. ICAPS (2022)
Alvaro Velasquez, K. Subramani, Piotr Wojciechowski
On the complexity of and solutions to the minimum stopping and trapping set problems. Theor. Comput. Sci. 915 (2022)
Sumit Kumar Jha, Rickard Ewetz, Alvaro Velasquez, Arvind Ramanathan, Susmit Jha
Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. AAAI (2022)
Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu
Resilient Constrained Consensus over Complete Graphs via Feasibility Redundancy. CoRR (2022)
K. Subramani, Piotr Wojciechowski, Alvaro Velasquez
New Results in Priority-Based Bin Packing. ALGOCLOUD (2022)
Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez
A Differentiable Approach to the Maximum Independent Set Problem Using Graph-Based Neural Network Structures. MLSP (2022)
Ismail R. Alkhouri, Stanley Bak, Alvaro Velasquez, George K. Atia
On the Coarse Robustness of Classifiers. IEEECONF (2022)
Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez
A differentiable approach to the maximum independent set problem using dataless neural networks. Neural Networks 155 (2022)
Yudan Wang, Yue Wang, Yi Zhou, Alvaro Velasquez, Shaofeng Zou
Data-Driven Robust Multi-Agent Reinforcement Learning. MLSP (2022)
Zenan Sun, Jingyi Su, Donghyun Jeon, Alvaro Velasquez, Houbing Song, Shuteng Niu
Reinforced Contrastive Graph Neural Networks (RCGNN) for Anomaly Detection. IPCCC (2022)
Alvaro Velasquez, Brett Bissey, Lior Barak, Daniel Melcer, Andre Beckus, Ismail Alkhouri, George K. Atia
Multi-Agent Tree Search with Dynamic Reward Shaping. ICAPS (2022)
Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu
Resilient Constrained Consensus over Complete Graphs via Feasibility Redundancy. ACC (2022)
Sumit Kumar Jha, Alvaro Velasquez, Rickard Ewetz, Laura Pullum, Susmit Jha
ExplainIt!: A Tool for Computing Robust Attributions of DNNs. IJCAI (2022)
Alvaro Velasquez, Ismail R. Alkhouri, Brett Bissey, Lior Barak, George K. Atia
The Minimum Value State Problem in Actor-Critic Networks. MLSP (2022)
Justus Renkhoff, Wenkai Tan, Alvaro Velasquez, William Yichen Wang, Yongxin Liu, Jian Wang, Shuteng Niu, Lejla Begic Fazlic, Guido Dartmann, Houbing Song
Exploring Adversarial Attacks on Neural Networks: An Explainable Approach. IPCCC (2022)
Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks. CoRR (2022)
Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia
Synthesis of Adversarial Samples in Two-Stage Classifiers. ICASSP (2022)
Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia
BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples. MLSP (2022)
Alvaro Velasquez, Ismail Alkhouri, Andre Beckus, Ashutosh Trivedi, George K. Atia
Controller Synthesis for Omega-Regular and Steady-State Specifications. AAMAS (2022)
Noah Topper, George K. Atia, Ashutosh Trivedi, Alvaro Velasquez
Active Grammatical Inference for Non-Markovian Planning. ICAPS (2022)
Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Alvaro Velasquez
Translating Omega-Regular Specifications to Average Objectives for Model-Free Reinforcement Learning. AAMAS (2022)
Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia
Adversarial Perturbation Attacks on Nested Dichotomies Classification Systems. MLSP (2021)
Sumit Kumar Jha, Rickard Ewetz, Alvaro Velasquez, Susmit Jha
On Smoother Attributions using Neural Stochastic Differential Equations. IJCAI (2021)
Alvaro Velasquez, Andre Beckus, Taylor Dohmen, Ashutosh Trivedi, Noah Topper, George K. Atia
Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes. CoRR (2021)
Edward Verenich, Tobias Martin, Alvaro Velasquez, Nazar Khan, Faraz Hussain
Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks. CoRR (2021)
Ismail Alkhouri, Alvaro Velasquez, George K. Atia
BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples. CoRR (2021)
Sumit Kumar Jha, Arvind Ramanathan, Rickard Ewetz, Alvaro Velasquez, Susmit Jha
Protein Folding Neural Networks Are Not Robust. CoRR (2021)
Alvaro Velasquez, Sumit Kumar Jha, Rickard Ewetz, Susmit Jha
Automated Synthesis of Quantum Circuits Using Symbolic Abstractions and Decision Procedures. ISCAS (2021)
Alvaro Velasquez, Brett Bissey, Lior Barak, Andre Beckus, Ismail Alkhouri, Daniel Melcer, George K. Atia
Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search. AAAI (2021)
Alvaro Velasquez, Ashutosh Trivedi, Ismail Alkhouri, Andre Beckus, George K. Atia
Controller Synthesis for Omega-Regular and Steady-State Specifications. CoRR (2021)
Piotr J. Wojciechowski, K. Subramani, Alvaro Velasquez, Bugra Caskurlu
Algorithmic Analysis of Priority-Based Bin Packing. CALDAM (2021)
K. Subramani, Piotr J. Wojciechowski, Alvaro Velasquez
On the Copy Complexity of Width 3 Horn Constraint Systems. FroCoS (2021)
George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez
Steady-State Planning in Expected Reward Multichain MDPs. J. Artif. Intell. Res. 72 (2021)
Jing Wang, Elias Wilson, Alvaro Velasquez
Consensus-Based Value Iteration for Multiagent Cooperative Control. CDC (2021)
Christopher H. Bennett, T. Patrick Xiao, Can Cui, Naimul Hassan, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Alvaro Velasquez, Joseph S. Friedman, Matthew J. Marinella
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning. ISCAS (2020)
George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez
Verifiable Planning in Expected Reward Multichain MDPs. CoRR (2020)
Wesley H. Brigner, Naimul Hassan, Xuan Hu, Christopher H. Bennett, Felipe García-Sánchez, Can Cui, Alvaro Velasquez, Matthew J. Marinella, Jean Anne C. Incorvia, Joseph S. Friedman
Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions. CoRR (2020)
George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez
Steady-State Policy Synthesis in Multichain Markov Decision Processes. IJCAI (2020)
Edward Verenich, Alvaro Velasquez, Nazar Khan, Faraz Hussain
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia. CoRR (2020)
Edward Verenich, Alvaro Velasquez, Nazar Khan, Faraz Hussain
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia. ICMLA (2020)
Sumit Kumar Jha, Susmit Jha, Rickard Ewetz, Sunny Raj, Alvaro Velasquez, Laura L. Pullum, Ananthram Swami
An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks. CoRR (2020)
Christopher H. Bennett, T. Patrick Xiao, Can Cui, Naimul Hassan, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Alvaro Velasquez, Joseph S. Friedman, Matthew J. Marinella
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning. CoRR (2020)
Alvaro Velasquez, Christopher H. Bennett, Naimul Hassan, Wesley H. Brigner, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Matthew J. Marinella, Joseph S. Friedman
Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alvaro Velasquez