Putting humpty-dumpty together: Mining causal mechanistic biochemical models from big data. - Faraz Hussain 001; Alvaro Velasquez; Emily Sassano; Sumit Kumar Jha 001 (ICCABS, 2014)

Parallel computing using memristive crossbar networks: Nullifying the processor-memory bottleneck. - Alvaro Velasquez; Sumit Kumar Jha 001 (IDT, 2014)

Fault-tolerant in-memory crossbar computing using quantified constraint solving. - Alvaro Velasquez; Sumit Kumar Jha 001 (ICCD, 2015)

Automated synthesis of crossbars for nanoscale computing using formal methods. - Alvaro Velasquez; Sumit Kumar Jha 001 (NANOARCH, 2015)

Flow-based computing on nanoscale crossbars: Design and implementation of full adders. - Zahiruddin Alamgir; Karsten Beckmann; Nathaniel C. Cady; Alvaro Velasquez; Sumit Kumar Jha 001 (ISCAS, 2016)

Parallel boolean matrix multiplication in linear time using rectifying memristors. - Alvaro Velasquez; Sumit Kumar Jha 001 (ISCAS, 2016)

The cardinality-constrained paths problem: Multicast data routing in heterogeneous communication networks. - Alvaro Velasquez; Piotr Wojciechowski 002; K. Subramani 001; Steven L. Drager 001; Sumit Kumar Jha 001 (NCA, 2016)

Computation of Boolean matrix chain products in 3D ReRAM. - Alvaro Velasquez; Sumit Kumar Jha 001 (ISCAS, 2017)

Minimization of Testing Costs in Capacity-Constrained Database Migration. - K. Subramani 001; Bugra Çaskurlu; Alvaro Velasquez (ALGOCLOUD, 2018)

In-memory computing using paths-based logic and heterogeneous components. - Alvaro Velasquez; Sumit Kumar Jha 001 (DATE, 2018)

3D Crosspoint Memory as a Parallel Architecture for Computing Network Reachability. - Alvaro Velasquez; Sumit Kumar Jha 001 (ICCD, 2018)

Finding Minimum Stopping and Trapping Sets: An Integer Linear Programming Approach. - Alvaro Velasquez; K. Subramani 001; Steven L. Drager 001 (ISCO, 2018)

Brief Announcement: Parallel Transitive Closure Within 3D Crosspoint Memory. - Alvaro Velasquez; Sumit Kumar Jha 001 (SPAA, 2018)

On the Susceptibility of Deep Neural Networks to Natural Perturbations. - Mesut Ozdag; Sunny Raj; Steven Lawrence Fernandes; Alvaro Velasquez; Laura Pullum; Sumit Kumar Jha 001 (AISafety@IJCAI, 2019)

Steady-State Policy Synthesis for Verifiable Control. - Alvaro Velasquez (IJCAI, 2019)

Spatially Efficient In-Memory Addition Through Destructive and Non-Destructive Operations. - Alvaro Velasquez; Benjamin Shaia (ISCAS, 2019)

Verification-Guided Tree Search. - Alvaro Velasquez; Daniel Melcer (AAMAS, 2020)

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia. - Edward Verenich; Alvaro Velasquez; Nazar Khan; Faraz Hussain 001 (ICMLA, 2020)

Steady-State Policy Synthesis in Multichain Markov Decision Processes. - George K. Atia; Andre Beckus; Ismail Alkhouri; Alvaro Velasquez (IJCAI, 2020)

Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning. - 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 (ISCAS, 2020)

FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints. - Edward Verenich; Alvaro Velasquez; M. G. Sarwar Murshed; Faraz Hussain 001 (OpML, 2020)

The Utility of Feature Reuse: Transfer Learning in Data-Starved Regimes. - Edward Verenich; Alvaro Velasquez; M. G. Sarwar Murshed; Faraz Hussain 001 (CoRR, 2020)

Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture. - Alvaro Velasquez; Christopher H. Bennett; Naimul Hassan; Wesley H. Brigner; Otitoaleke G. Akinola; Jean Anne C. Incorvia; Matthew J. Marinella; Joseph S. Friedman (CoRR, 2020)

An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Sunny Raj; Alvaro Velasquez; Laura L. Pullum; Ananthram Swami (CoRR, 2020)

Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions. - Wesley H. Brigner; Naimul Hassan; Xuan Hu 002; Christopher H. Bennett; Felipe García-Sánchez; Can Cui; Alvaro Velasquez; Matthew J. Marinella; Jean Anne C. Incorvia; Joseph S. Friedman (CoRR, 2020)

Verifiable Planning in Expected Reward Multichain MDPs. - George K. Atia; Andre Beckus; Ismail Alkhouri; Alvaro Velasquez (CoRR, 2020)

Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search. - Alvaro Velasquez; Brett Bissey; Lior Barak; Andre Beckus; Ismail Alkhouri; Daniel Melcer; George K. Atia (AAAI, 2021)

Algorithmic Analysis of Priority-Based Bin Packing. - Piotr Wojciechowski 002; K. Subramani 001; Alvaro Velasquez; Bugra Çaskurlu (CALDAM, 2021)

Consensus-Based Value Iteration for Multiagent Cooperative Control. - Jing Wang 005; Elias Wilson; Alvaro Velasquez (CDC, 2021)

On the Copy Complexity of Width 3 Horn Constraint Systems. - K. Subramani 001; Piotr Wojciechowski 002; Alvaro Velasquez (FroCoS, 2021)

On Smoother Attributions using Neural Stochastic Differential Equations. - Sumit Kumar Jha 001; Rickard Ewetz; Alvaro Velasquez; Susmit Jha (IJCAI, 2021)

Automated Synthesis of Quantum Circuits Using Symbolic Abstractions and Decision Procedures. - Alvaro Velasquez; Sumit Kumar Jha 001; Rickard Ewetz; Susmit Jha (ISCAS, 2021)

Adversarial Perturbation Attacks on Nested Dichotomies Classification Systems. - Ismail R. Alkhouri; Alvaro Velasquez; George K. Atia (MLSP, 2021)

Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes. - Alvaro Velasquez; Andre Beckus; Taylor Dohmen; Ashutosh Trivedi 001; Noah Topper; George K. Atia (CoRR, 2021)

Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks. - Edward Verenich; Tobias Martin; Alvaro Velasquez; Nazar Khan; Faraz Hussain 001 (CoRR, 2021)

Protein Folding Neural Networks Are Not Robust. - Sumit Kumar Jha 001; Arvind Ramanathan; Rickard Ewetz; Alvaro Velasquez; Susmit Jha (CoRR, 2021)

Steady-State Planning in Expected Reward Multichain MDPs. - George K. Atia; Andre Beckus; Ismail Alkhouri; Alvaro Velasquez (J. Artif. Intell. Res., 2021)

Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. - Sumit Kumar Jha 001; Rickard Ewetz; Alvaro Velasquez; Arvind Ramanathan; Susmit Jha (AAAI, 2022)

On the Coarse Robustness of Classifiers. - Ismail R. Alkhouri; Stanley Bak; Alvaro Velasquez; George K. Atia (IEEECONF, 2022)

Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning. - Taylor Dohmen; Noah Topper; George K. Atia; Andre Beckus; Ashutosh Trivedi 001; Alvaro Velasquez (ICAPS, 2022)

Active Grammatical Inference for Non-Markovian Planning. - Noah Topper; George K. Atia; Ashutosh Trivedi 001; Alvaro Velasquez (ICAPS, 2022)

Multi-Agent Tree Search with Dynamic Reward Shaping. - Alvaro Velasquez; Brett Bissey; Lior Barak; Daniel Melcer; Andre Beckus; Ismail Alkhouri; George K. Atia (ICAPS, 2022)

New Results in Priority-Based Bin Packing. - K. Subramani 001; Piotr Wojciechowski 002; Alvaro Velasquez (ALGOCLOUD, 2022)

Resilient Constrained Consensus over Complete Graphs via Feasibility Redundancy. - Jingxuan Zhu; Yixuan Lin; Alvaro Velasquez; Ji Liu 001 (ACC, 2022)

Translating Omega-Regular Specifications to Average Objectives for Model-Free Reinforcement Learning. - Milad Kazemi; Mateo Perez; Fabio Somenzi; Sadegh Soudjani; Ashutosh Trivedi 001; Alvaro Velasquez (AAMAS, 2022)

Controller Synthesis for Omega-Regular and Steady-State Specifications. - Alvaro Velasquez; Ismail Alkhouri; Andre Beckus; Ashutosh Trivedi 001; George K. Atia (AAMAS, 2022)

On the Approximability of Path and Cycle Problems in Arc-Dependent Networks. - Piotr Wojciechowski 002; K. Subramani 001; Alvaro Velasquez; Matthew D. Williamson (CALDAM, 2022)

Analyzing the Reachability Problem in Choice Networks. - Piotr Wojciechowski 002; K. Subramani 001; Alvaro Velasquez (CPAIOR, 2022)

Synthesis of Adversarial Samples in Two-Stage Classifiers. - Ismail R. Alkhouri; Alvaro Velasquez; George K. Atia (ICASSP, 2022)

ExplainIt!: A Tool for Computing Robust Attributions of DNNs. - Sumit Kumar Jha 001; Alvaro Velasquez; Rickard Ewetz; Laura Pullum; Susmit Jha (IJCAI, 2022)

Exploring Adversarial Attacks on Neural Networks: An Explainable Approach. - Justus Renkhoff; Wenkai Tan; Alvaro Velasquez; William Yichen Wang; Yongxin Liu; Jian Wang 061; Shuteng Niu; Lejla Begic Fazlic; Guido Dartmann; Houbing Song (IPCCC, 2022)

Reinforced Contrastive Graph Neural Networks (RCGNN) for Anomaly Detection. - Zenan Sun; Jingyi Su; Donghyun Jeon; Alvaro Velasquez; Houbing Song; Shuteng Niu (IPCCC, 2022)

A Differentiable Approach to the Maximum Independent Set Problem Using Graph-Based Neural Network Structures. - Ismail R. Alkhouri; George K. Atia; Alvaro Velasquez (MLSP, 2022)

BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples. - Ismail R. Alkhouri; Alvaro Velasquez; George K. Atia (MLSP, 2022)

The Minimum Value State Problem in Actor-Critic Networks. - Alvaro Velasquez; Ismail R. Alkhouri; Brett Bissey; Lior Barak; George K. Atia (MLSP, 2022)

Data-Driven Robust Multi-Agent Reinforcement Learning. - Yudan Wang; Yue Wang 068; Yi Zhou 017; Alvaro Velasquez; Shaofeng Zou (MLSP, 2022)

A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks. - Ismail R. Alkhouri; George K. Atia; Alvaro Velasquez (CoRR, 2022)

Resilient Distributed Optimization. - Jingxuan Zhu; Yixuan Lin; Alvaro Velasquez; Ji Liu 001 (CoRR, 2022)

A differentiable approach to the maximum independent set problem using dataless neural networks. - Ismail R. Alkhouri; George K. Atia; Alvaro Velasquez (Neural Networks, 2022)

On the complexity of and solutions to the minimum stopping and trapping set problems. - Alvaro Velasquez; K. Subramani 001; Piotr Wojciechowski 002 (Theor. Comput. Sci., 2022)

Robust Average-Reward Markov Decision Processes. - Yue Wang 068; Alvaro Velasquez; George K. Atia; Ashley Prater-Bennette; Shaofeng Zou (AAAI, 2023)

Automaton-Guided Curriculum Generation for Reinforcement Learning Agents. - Yash Shukla; Abhishek Kulkarni; Robert Wright; Alvaro Velasquez; Jivko Sinapov (ICAPS, 2023)

Resilient Distributed Optimization*. - Jingxuan Zhu; Yixuan Lin; Alvaro Velasquez; Ji Liu 001 (ACC, 2023)

LTL-Based Non-Markovian Inverse Reinforcement Learning. - Mohammad Afzal; Sankalp Gambhir; Ashutosh Gupta; S. Krishna 004; Ashutosh Trivedi 001; Alvaro Velasquez (AAMAS, 2023)

A Resilient Distributed Algorithm for Solving Linear Equations. - Jingxuan Zhu; Alvaro Velasquez; Ji Liu 001 (CDC, 2023)

Differentiable Discrete Optimization Using Dataless Neural Networks. - Sangram Kishor Jena; K. Subramani 001; Alvaro Velasquez (COCOA (2), 2023)

The Octatope Abstract Domain for Verification of Neural Networks. - Stanley Bak; Taylor Dohmen; K. Subramani 001; Ashutosh Trivedi 001; Alvaro Velasquez; Piotr Wojciechowski 002 (FM, 2023)

NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks. - Wenkai Tan; Justus Renkhoff; Alvaro Velasquez; Ziyu Wang; Lusi Li; Jian Wang 061; Shuteng Niu; Fan Yang; Yongxin Liu; Houbing Song (FUZZ, 2023)

Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting. - Susmit Jha; Sumit Kumar Jha 001; Patrick Lincoln; Nathaniel D. Bastian; Alvaro Velasquez; Sandeep Neema (ICAA, 2023)

SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection. - Lijing Zhu; Qizhen Lan; Alvaro Velasquez; Houbing Song; Acharya Kamal; Qing Tian 003; Shuteng Niu (ICDM (Workshops), 2023)

Model-Free Robust Average-Reward Reinforcement Learning. - Yue Wang 068; Alvaro Velasquez; George K. Atia; Ashley Prater-Bennette; Shaofeng Zou (ICML, 2023)

A Non-Targeted Attack Approach for the Coarse Misclassification Problem. - Ismail R. Alkhouri; Alvaro Velasquez; George K. Atia (IJCNN, 2023)

Neural SDEs for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (MILCOM, 2023)

Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving. - Sumit Kumar Jha 001; Susmit Jha; Patrick Lincoln; Nathaniel D. Bastian; Alvaro Velasquez; Rickard Ewetz; Sandeep Neema (MILCOM, 2023)

On the Robustness of AlphaFold: A COVID-19 Case Study. - Ismail Alkhouri; Sumit Kumar Jha 001; Andre Beckus; George K. Atia; Alvaro Velasquez; Rickard Ewetz; Arvind Ramanathan; Susmit Jha (CoRR, 2023)

Safety Margins for Reinforcement Learning. - Alexander Grushin; Walt Woods; Alvaro Velasquez; Simon Khan (CoRR, 2023)

Neural Stochastic Differential Equations for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (CoRR, 2023)

Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving. - Sumit Kumar Jha 001; Susmit Jha; Patrick Lincoln; Nathaniel D. Bastian; Alvaro Velasquez; Rickard Ewetz; Sandeep Neema (CoRR, 2023)

Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning. - Suraj Singireddy; Andre Beckus; George K. Atia; Sumit Kumar Jha 001; Alvaro Velasquez (CoRR, 2023)

Optimal Deterministic Controller Synthesis from Steady-State Distributions. - Alvaro Velasquez; Ismail Alkhouri; K. Subramani 001; Piotr Wojciechowski 002; George K. Atia (J. Autom. Reason., 2023)

Reachability in choice networks. - Piotr Wojciechowski 002; K. Subramani 001; Alvaro Velasquez (Discret. Optim., 2023)

Reachability problems in interval-constrained and cardinality-constrained graphs. - Alvaro Velasquez; K. Subramani 001; Piotr Wojciechowski 002 (Discret. Math. Algorithms Appl., 2023)

Artifact for "Assume-Guarantee Reinforcement Learning". - Milad Kazemi Mehrabadi; Mateo Perez; Fabio Somenzi; Sadegh Soudjani; Ashutosh Trivedi 001; Alvaro Velasquez (Zenodo, 2023)

Assume-Guarantee Reinforcement Learning. - Milad Kazemi; Mateo Perez; Fabio Somenzi; Sadegh Soudjani; Ashutosh Trivedi 001; Alvaro Velasquez (AAAI, 2024)

LgTS: Dynamic Task Sampling using LLM-generated Sub-Goals for Reinforcement Learning Agents. - Yash Shukla; Wenchang Gao; Vasanth Sarathy; Alvaro Velasquez; Robert Wright; Jivko Sinapov (AAMAS, 2024)

KGIF: Optimizing Relation-Aware Recommendations with Knowledge Graph Information Fusion. - Donghyun Jeon; Wenbo Sun; Houbing Herbert Song; Dongfang Liu; Alvaro Velasquez; Chloe Yixin Xie; Shuteng Niu (IEEE Big Data, 2024)

An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning. - Calvin Nau; Prashant Sankaran; Moises Sudit; Payam Khazaelpour; Katie McConky; Alvaro Velasquez; Liise Kayler (CogSIMA, 2024)

On the Design of Novel Attention Mechanism for Enhanced Efficiency of Transformers. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (DAC, 2024)

TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection. - Hanning Chen; Wenjun Huang 001; Yang Ni 001; Sanggeon Yun; Yezi Liu; Fei Wen; Alvaro Velasquez; Hugo Latapie; Mohsen Imani (ECCV Workshops (20), 2024)

Solving Mystery Planning Problems Using Category Theory, Functors, and Large Language Models. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (ICAA, 2024)

SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments. - Abhinav Rajvanshi; Karan Sikka; Xiao Lin; Bhoram Lee; Han-Pang Chiu; Alvaro Velasquez (ICAPS, 2024)

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. - Yash Shukla; Tanushree Burman; Abhishek Kulkarni; Robert Wright; Alvaro Velasquez; Jivko Sinapov (ICAPS, 2024)

A Differential Approach for Several NP-hard Optimization Problems. - Sangram Kishor Jena; K. Subramani 001; Alvaro Velasquez (ISAIM, 2024)

Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm. - Kamal Acharya 001; Alvaro Velasquez; Yongxin Liu; Dahai Liu; Liang Sun; Houbing Herbert Song (ITSC, 2024)

Neuro-symbolic Generative AI Assistant for System Design. - Susmit Jha; Sumit Kumar Jha 001; Alvaro Velasquez (MEMOCODE, 2024)

Co-Synthesis of Code and Formal Models Using Large Language Models and Functors. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (MILCOM, 2024)

On the Hardness of Decentralized Multi-Agent Policy Evaluation Under Byzantine Attacks. - Hairi; Minghong Fang; Zifan Zhang; Alvaro Velasquez; Jia Liu 002 (WiOpt, 2024)

Hyperdimensional Quantum Factorization. - Prathyush Poduval; Zhuowen Zou; Alvaro Velasquez; Mohsen Imani (CoRR, 2024)

Bayesian Inverse Reinforcement Learning for Non-Markovian Rewards. - Noah Topper; Alvaro Velasquez; George K. Atia (CoRR, 2024)

Dataless Quadratic Neural Networks for the Maximum Independent Set Problem. - Ismail Alkhouri; Cedric Le Denmat; Yingjie Li; Cunxi Yu; Jia Liu; Rongrong Wang; Alvaro Velasquez (CoRR, 2024)

Combining AI Control Systems and Human Decision Support via Robustness and Criticality. - Walt Woods; Alexander Grushin; Simon Khan; Alvaro Velasquez (CoRR, 2024)

LLMs as Probabilistic Minimally Adequate Teachers for DFA Learning. - Lekai Chen; Ashutosh Trivedi 001; Alvaro Velasquez (CoRR, 2024)

Bioinformatics Retrieval Augmentation Data (BRAD) Digital Assistant. - Joshua Pickard; Marc Andrew Choi; Natalie Oliven; Cooper Stansbury; Jillian Cwycyshyn; Nicholas Galioto; Alex A. Gorodetsky; Alvaro Velasquez; Indika Rajapakse (CoRR, 2024)

Criticality and Safety Margins for Reinforcement Learning. - Alexander Grushin; Walt Woods; Alvaro Velasquez; Simon Khan (CoRR, 2024)

Imperceptible Adversarial Examples in the Physical World. - Weilin Xu; Sebastian Szyller; Cory Cornelius; Luis Murillo Rojas; Marius Arvinte; Alvaro Velasquez; Jason Martin; Nageen Himayat (CoRR, 2024)

Robust Average-Reward Reinforcement Learning. - Yue Wang 068; Alvaro Velasquez; George K. Atia; Ashley Prater-Bennette; Shaofeng Zou (J. Artif. Intell. Res., 2024)

Byzantine-Resilient Decentralized Multi-Armed Bandits. - Jingxuan Zhu; Alec Koppel; Alvaro Velasquez; Ji Liu 001 (Trans. Mach. Learn. Res., 2024)

Priority-based bin packing with subset constraints. - Piotr Wojciechowski 002; K. Subramani 001; Alvaro Velasquez; Bugra Çaskurlu (Discret. Appl. Math., 2024)

Farkas Bounds on Horn Constraint Systems. - K. Subramani 001; Piotr Wojciechowski 002; Alvaro Velasquez (Theory Comput. Syst., 2024)

Neurosymbolic Reinforcement Learning and Planning: A Survey. - Kamal Acharya 001; Waleed Raza; Carlos M. J. M. Dourado Júnior; Alvaro Velasquez; Houbing Herbert Song (IEEE Trans. Artif. Intell., 2024)

Controller synthesis for linear temporal logic and steady-state specifications. - Alvaro Velasquez; Ismail Alkhouri; Andre Beckus; Ashutosh Trivedi 001; George K. Atia (Auton. Agents Multi Agent Syst., 2024)

Arc-dependent networks: theoretical insights and a computational study. - Alvaro Velasquez; Piotr Wojciechowski 002; K. Subramani 001; Matthew D. Williamson (Ann. Oper. Res., 2024)

Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences. - Ismail R. Alkhouri; Sumit Kumar Jha 001; Andre Beckus; George K. Atia; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (IEEE Trans. Artif. Intell., 2024)

A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence. - Justus Renkhoff; Ke Feng; Marc Meier-Doernberg; Alvaro Velasquez; Houbing Herbert Song (IEEE Trans. Artif. Intell., 2024)

The hexatope and octatope abstract domains for neural network verification. - Stanley Bak; Taylor Dohmen; K. Subramani 001; Ashutosh Trivedi 001; Alvaro Velasquez; Piotr Wojciechowski 002 (Formal Methods Syst. Des., 2024)

Designing dataless neural networks for kidney exchange variants. - Sangram K. Jena 001; K. Subramani 001; Alvaro Velasquez (Neural Comput. Appl., 2024)

A Survey on Symbolic Knowledge Distillation of Large Language Models. - Kamal Acharya 001; Alvaro Velasquez; Houbing Herbert Song (IEEE Trans. Artif. Intell., 2024)

Immune: Improving Safety Against Jailbreaks in Multi-modal LLMs via Inference-Time Alignment. - Soumya Suvra Ghosal; Souradip Chakraborty; Vaibhav Singh; Tianrui Guan; Mengdi Wang; Ahmad Beirami; Furong Huang; Alvaro Velasquez; Dinesh Manocha; Amrit Singh Bedi (CVPR, 2025)

Hybrid Offline Passive Grammatical Inference and Online Planning for Non-Markovian Tasks. - Mahyar Alinejad; Alvaro Velasquez; Yue Wang 068; George K. Atia (ICASSP, 2025)

Bidirectional End-to-End Framework for Transfer from Abstract Models in Non-Markovian Reinforcement Learning. - Mahyar Alinejad; Precious Nwaorgu; Chinwendu Enyioha; Yue Wang 068; Alvaro Velasquez; George Atia (NeuS, 2025)

KGAccel: A Domain-Specific Reconfigurable Accelerator for Knowledge Graph Reasoning. - Hanning Chen; Ali Zakeri; Yang Ni 001; Fei Wen; Behnam Khaleghi; Hugo Latapie; Alvaro Velasquez; Mohsen Imani (NeuS, 2025)

Zero-Shot Detection of Out-of-Context Objects Using Foundation Models. - Anirban Roy; Adam D. Cobb; Ramneet Kaur; Sumit Jha 001; Nathaniel D. Bastian; Alexander M. Berenbeim; Robert H. Thomson 001; Iain Cruickshank; Alvaro Velasquez; Susmit Jha (WACV, 2025)

Models for Test Cost Minimization in Database Migration. - Bugra Çaskurlu; K. Subramani 001; Utku Umur Acikalin; Alvaro Velasquez; Piotr Wojciechowski 002 (INFORMS J. Comput., 2025)

ANSR-DT: An Adaptive Neuro-Symbolic Learning and Reasoning Framework for Digital Twins. - Safayat Bin Hakim; Muhammad Adil 002; Alvaro Velasquez; Houbing Herbert Song (CoRR, 2025)

A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Models. - Longchao Da; Justin Turnau; Thirulogasankar Pranav Kutralingam; Alvaro Velasquez; Paulo Shakarian; Hua Wei 001 (CoRR, 2025)

From Abstraction to Reality: DARPA's Vision for Robust Sim-to-Real Autonomy. - Erfaun Noorani; Zachary Serlin; Ben Price; Alvaro Velasquez (CoRR, 2025)

A Dataless Reinforcement Learning Approach to Rounding Hyperplane Optimization for Max-Cut. - Gabriel Malikal; Ismail Alkhouri; Alvaro Velasquez; Adam M. Alessio; Saiprasad Ravishankar (CoRR, 2025)

Average Reward Reinforcement Learning for Omega-Regular and Mean-Payoff Objectives. - Milad Kazemi; Mateo Perez; Fabio Somenzi; Sadegh Soudjani; Ashutosh Trivedi 001; Alvaro Velasquez (CoRR, 2025)

Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning. - Zhiyao Zhang; Myeung Suk Oh; Hairi; Ziyue Luo; Alvaro Velasquez; Jia Liu 002 (CoRR, 2025)

TOGA: Temporally Grounded Open-Ended Video QA with Weak Supervision. - Ayush Gupta; Anirban Roy; Rama Chellappa; Nathaniel D. Bastian; Alvaro Velasquez; Susmit Jha (CoRR, 2025)

Efficient Neuro-Symbolic Retrieval-Augmented Generation through Adaptive Query Routing. - Safayat Bin Hakim; Muhammad Adil 002; Alvaro Velasquez; Houbing Herbert Song (CoRR, 2025)

Correction to: Farkas Bounds on Horn Constraint Systems. - K. Subramani 001; Piotr Wojciechowski 002; Alvaro Velasquez (Theory Comput. Syst., 2025)

Foundation Models for Logistics: Toward Certifiable, Conversational Planning Interfaces. - Yunhao Yang; Neel P. Bhatt; Christian Ellis; Alvaro Velasquez; Zhangyang Wang; Ufuk Topcu (CoRR, 2025)

DEM-NeRF: A Neuro-Symbolic Method for Scientific Discovery through Physics-Informed Simulation. - Wenkai Tan; Alvaro Velasquez; Houbing Song (CoRR, 2025)

Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimization. - Myeung Suk Oh; Zhiyao Zhang; FNU Hairi; Alvaro Velasquez; Jia Liu 002 (CoRR, 2025)