Chemical plume detection in hyperspectral imagery via joint sparse representation. - Minh Dao; Dzung T. Nguyen; Trac D. Tran; Sang Chin 001 (MILCOM, 2012)

A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements. - Guangliang Chen; Mark A. Iwen; Sang Chin 001; Mauro Maggioni (VCIP, 2012)

Real Time Compressive Sensing Video Reconstruction in Hardware. - Garrick Orchard; Jie Zhang 063; Yuanming Suo; Minh Dao; Dzung T. Nguyen; Sang Chin 001; Christoph Posch; Trac D. Tran; Ralph Etienne-Cummings (IEEE J. Emerg. Sel. Topics Circuits Syst., 2012)

Energy-efficient two-stage Compressed Sensing method for implantable neural recordings. - Yuanming Suo; Jie Zhang 063; Ralph Etienne-Cummings; Trac D. Tran; Sang Chin 001 (BioCAS, 2013)

Video frame interpolation via weighted robust principal component analysis. - Minh Dao; Yuanming Suo; Sang Chin 001; Trac D. Tran (ICASSP, 2013)

Reconstruction of neural action potentials using signal dependent sparse representations. - Jie Zhang 063; Yuanming Suo; Srinjoy Mitra; Sang (Peter) Chin; Trac D. Tran; Refet Firat Yazicioglu; Ralph Etienne-Cummings (ISCAS, 2013)

Structured sparse representation with low-rank interference. - Minh Dao; Yuanming Suo; Sang (Peter) Chin; Trac D. Tran (ACSSC, 2014)

A dictionary learning algorithm for multi-channel neural recordings. - Tao Xiong; Yuanming Suo; Jie Zhang 063; Siwei Liu 004; Ralph Etienne-Cummings; Sang Chin 001; Trac D. Tran (BioCAS, 2014)

Computing Diffusion State Distance Using Green's Function and Heat Kernel on Graphs. - Edward Boehnlein; Peter Chin 001; Amit Sinha; Linyuan Lu (WAW, 2014)

Energy-Efficient Multi-Mode Compressed Sensing System for Implantable Neural Recordings. - Yuanming Suo; Jie Zhang 063; Tao Xiong; Sang Peter Chin; Ralph Etienne-Cummings; Trac D. Tran (IEEE Trans. Biomed. Circuits Syst., 2014)

An Efficient and Compact Compressed Sensing Microsystem for Implantable Neural Recordings. - Jie Zhang 063; Yuanming Suo; Srinjoy Mitra; Sang (Peter) Chin; Steven Hsiao; Refet Firat Yazicioglu; Trac D. Tran; Ralph Etienne-Cummings (IEEE Trans. Biomed. Circuits Syst., 2014)

Targeted Dot Product Representation for Friend Recommendation in Online Social Networks. - Minh D. Dao; Akshay Rangamani; Sang Peter Chin; Nam P. Nguyen; Trac D. Tran (ASONAM, 2015)

Compressed sensing block-wise exposure control algorithm using optical flow estimation. - Tao Xiong; Jie Zhang 063; Sang Chin 001; Trac D. Tran; Ralph Etienne-Cummings (BioCAS, 2015)

High-speed compressed sensing measurement using spectrally-encoded ultrafast laser pulses. - Bryan T. Bosworth; Jasper R. Stroud; Dung N. Tran; Trac D. Tran; Sang Chin 001; Mark A. Foster (CISS, 2015)

Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture. - Daniel R. Mendat; Sang Chin 001; Steve B. Furber; Andreas G. Andreou (CISS, 2015)

Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recovery. - Peter Chin 001; Anup Rao 002; Van Vu (COLT, 2015)

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system. - Lei H. Hamilton; Marc W. McConley; Kai Angermueller; David Goldberg 003; Massimiliano Corba; Louis Y. Kim; James Moran; Philip D. Parks; Sang (Peter) Chin; Alik S. Widge; Darin D. Dougherty; Emad N. Eskandar (EMBC, 2015)

Nonnegative matrix factorization with gradient vertex pursuit. - Dung N. Tran; Tao Xiong; Sang Peter Chin; Trac D. Tran (ICASSP, 2015)

Local sensing with global recovery. - Dung N. Tran; Duyet N. Tran; Sang Peter Chin; Trac D. Tran (ICIP, 2015)

Randomized Minmax Regret for Combinatorial Optimization Under Uncertainty. - Andrew Mastin; Patrick Jaillet; Sang Chin 001 (ISAAC, 2015)

An unsupervised dictionary learning algorithm for neural recordings. - Tao Xiong; Jie Zhang 063; Yuanming Suo; Dung N. Tran; Ralph Etienne-Cummings; Sang Chin 001; Trac D. Tran (ISCAS, 2015)

Predicting local field potentials with recurrent neural networks. - Louis Y. Kim; Jacob Harer; Akshay Rangamani; James Moran; Philip D. Parks; Alik Widge; Emad N. Eskandar; Darin D. Dougherty; Sang (Peter) Chin (EMBC, 2016)

Compressive coding via random replicate mirror. - Dung N. Tran; Luoluo Liu; Trac D. Tran; Sang (Peter) Chin; Jeffrey Korn; Eric T. Hoke (GlobalSIP, 2016)

Partial face recognition: A sparse representation-based approach. - Luoluo Liu; Trac D. Tran; Sang (Peter) Chin (ICASSP, 2016)

Low-rank matrices recovery via entropy function. - Dung N. Tran; Shuai Huang; Sang Peter Chin; Trac D. Tran (ICASSP, 2016)

Neuromorphic sampling on the SpiNNaker and parallella chip multiprocessors. - Daniel R. Mendat; Sang Chin 001; Steve B. Furber; Andreas G. Andreou (LASCAS, 2016)

Wi(deband)-Fi: A Proposal for an Opportunistic Wideband Architecture based on Wi-Fi. - Guevara Noubir; Muriel Médard; Peter Chin 001 (MobiWac, 2016)

Topological and statistical behavior classifiers for tracking applications. - Paul Bendich; Sang Peter Chin; Jesse Clarke; Jonathan deSena; John Harer; Elizabeth Munch; Andrew Newman; David Porter; David Rouse; Nate Strawn; Adam Watkins (IEEE Trans. Aerosp. Electron. Syst., 2016)

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface. - Xilin Liu; Milin Zhang 001; Tao Xiong; Andrew G. Richardson; Timothy H. Lucas; Sang Peter Chin; Ralph Etienne-Cummings; Trac D. Tran; Jan Van der Spiegel (IEEE Trans. Biomed. Circuits Syst., 2016)

Domain specific inpainting with concurrently pretrained generative adversarial networks. - Xiao Zhou; Chengchen Wang; Yiteng Xu; Xiao Wang 028; Peter Chin 001 (GlobalSIP, 2017)

A provable nonconvex model for factoring nonnegative matrices. - Dung N. Tran; Sang Peter Chin; Trac D. Tran (ICASSP, 2017)

Automatic Vertebra Labeling in Large-Scale 3D CT Using Deep Image-to-Image Network with Message Passing and Sparsity Regularization. - Dong Yang 005; Tao Xiong; Daguang Xu; Qiangui Huang; David Liu 001; Shaohua Kevin Zhou; Zhoubing Xu; Jin Hyeong Park; Mingqing Chen; Trac D. Tran; Sang Peter Chin; Dimitris N. Metaxas; et al. (IPMI, 2017)

Live demonstration: A compact all-CMOS spatiotemporal compressed sensing video camera. - Tao Xiong; Jie Zhang 063; Chetan Singh Thakur; John M. Rattray; Sang Peter Chin; Trac D. Tran; Ralph Etienne-Cummings (ISCAS, 2017)

Deep Image-to-Image Recurrent Network with Shape Basis Learning for Automatic Vertebra Labeling in Large-Scale 3D CT Volumes. - Dong Yang 005; Tao Xiong; Daguang Xu; Shaohua Kevin Zhou; Zhoubing Xu; Mingqing Chen; Jin Hyeong Park; Sasa Grbic; Trac D. Tran; Sang Peter Chin; Dimitris N. Metaxas; Dorin Comaniciu (MICCAI (3), 2017)

Spatiotemporal compressed sensing for video compression. - Tao Xiong; John M. Rattray; Jie Zhang 063; Chetan Singh Thakur; Sang Peter Chin; Trac D. Tran; Ralph Etienne-Cummings (MWSCAS, 2017)

Critical Points Of An Autoencoder Can Provably Recover Sparsely Used Overcomplete Dictionaries. - Akshay Rangamani; Anirbit Mukherjee; Ashish Arora; Tejaswini Ganapathy; Amitabh Basu; Sang (Peter) Chin; Trac D. Tran (CoRR, 2017)

A Mathematical Analysis of Network Controllability Through Driver Nodes. - Sang Peter Chin; Jonathan Cohen; Alison Albin; Mykola Hayvanovych; Elizabeth Reilly; Gavin Brown 003; Jacob Harer (IEEE Trans. Comput. Soc. Syst., 2017)

Tree Structured Multimedia Signal Modeling. - Weicheng Ma; Kai Cao 005; Xiang Li 066; Peter Chin 001 (FLAIRS, 2018)

Reconstruction-Free Deep Convolutional Neural Networks for Partially Observed Images. - Arun Asokan Nair; Luoluo Liu; Akshay Rangamani; Peter Chin 001; Muyinatu A. Lediju Bell; Trac D. Tran (GlobalSIP, 2018)

A Greedy Pursuit Algorithm for Separating Signals from Nonlinear Compressive Observations. - Sang (Peter) Chin; Trac D. Tran; Dung N. Tran; Akshay Rangamani (ICASSP, 2018)

Defensive dropout for hardening deep neural networks under adversarial attacks. - Siyue Wang; Xiao Wang 028; Pu Zhao 001; Wujie Wen; David R. Kaeli; Peter Chin 001; Xue Lin 001 (ICCAD, 2018)

Using Deep Learning to Extract Scenery Information in Real Time Spatiotemporal Compressed Sensing. - Xiao Wang 028; Jie Zhang 063; Tao Xiong; Trac Duy Tran; Sang Peter Chin; Ralph Etienne-Cummings (ISCAS, 2018)

Sparse Coding and Autoencoders. - Akshay Rangamani; Anirbit Mukherjee; Amitabh Basu; Ashish Arora; Tejaswini Ganapathi; Sang (Peter) Chin; Trac D. Tran (ISIT, 2018)

Sound Signal Processing with Seq2Tree Network. - Weicheng Ma; Kai Cao 005; Zhaoheng Ni; Peter Chin 001; Xiang Li 066 (LREC, 2018)

Learning to Repair Software Vulnerabilities with Generative Adversarial Networks. - Jacob Harer; Onur Ozdemir; Tomo Lazovich; Christopher P. Reale; Rebecca L. Russell; Louis Y. Kim; Peter Chin 001 (NeurIPS, 2018)

Automated software vulnerability detection with machine learning. - Jacob A. Harer; Louis Y. Kim; Rebecca L. Russell; Onur Ozdemir; Leonard R. Kosta; Akshay Rangamani; Lei H. Hamilton; Gabriel I. Centeno; Jonathan R. Key; Paul M. Ellingwood; Marc W. McConley; Jeffrey M. Opper; et al. (CoRR, 2018)

Reducing Sampling Ratios and Increasing Number of Estimates Improve Bagging in Sparse Regression. - Luoluo Liu; Sang Peter Chin; Trac D. Tran (CISS, 2019)

Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses. - Xiao Wang 028; Siyue Wang; Pin-Yu Chen; Yanzhi Wang; Brian Kulis; Xue Lin 001; Sang Chin 001 (IJCAI, 2019)

JOBS: Joint-Sparse Optimization from Bootstrap Samples. - Luoluo Liu; Sang Peter Chin; Trac D. Tran (ISIT, 2019)

NodeDrop: A Condition for Reducing Network Size without Effect on Output. - Louis Jensen; Jacob Harer; Sang Chin 001 (CoRR, 2019)

Tree-Transformer: A Transformer-Based Method for Correction of Tree-Structured Data. - Jacob Harer; Christopher P. Reale; Peter Chin 001 (CoRR, 2019)

Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450. - Xavier F. Cadet; Réda Dehak; Sang Peter Chin; Miloud Bessafi (Entropy, 2019)

AdvMS: A Multi-Source Multi-Cost Defense Against Adversarial Attacks. - Xiao Wang 028; Siyue Wang; Pin-Yu Chen; Xue Lin 001; Peter Chin 001 (ICASSP, 2020)

NodeDrop: A Method for Finding Sufficient Network Architecture Size. - Louis Jensen; Jacob Harer; Sang Chin 001 (IJCNN, 2020)

A Study of Pyramid Structure for Code Correction. - Shan Huang; Xiao Zhou; Sang Chin 001 (CoRR, 2020)

Block Switching: A Stochastic Approach for Deep Learning Security. - Xiao Wang 028; Siyue Wang; Pin-Yu Chen; Xue Lin 001; Peter Chin 001 (CoRR, 2020)

Reinforcement Learning in FlipIt. - Laura Greige; Peter Chin 001 (CoRR, 2020)

GymFG: A Framework with a Gym Interface for FlightGear. - Andrew Wood; Ali Sydney; Peter Chin 001; Bishal Thapa; Ryan Ross (CoRR, 2020)

RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations. - Pedro Colon-Hernandez; Yida Xin; Henry Lieberman; Catherine Havasi; Cynthia Breazeal; Peter Chin 001 (ACL/IJCNLP (Findings), 2021)

Intrinsic Examples: Robust Fingerprinting of Deep Neural Networks. - Siyue Wang; Pu Zhao 001; Xiao Wang 028; Sang Chin 001; Thomas Wahl; Yunsi Fei; Qi Alfred Chen; Xue Lin 001 (BMVC, 2021)

Neural-Guided, Bidirectional Program Search for Abstraction and Reasoning. - Simon Alford; Anshula Gandhi; Akshay Rangamani; Andrzej Banburski; Tony Wang; Sylee Dandekar; John Chin; Tomaso A. Poggio; Peter Chin 001 (COMPLEX NETWORKS, 2021)

Drug Repurposing Using Link Prediction on Knowledge Graphs with Applications to Non-volatile Memory. - Sarel Cohen; Moshik Hershcovitch; Martin Taraz; Otto Kißig; Andrew Wood; Daniel G. Waddington; Peter Chin 001; Tobias Friedrich 001 (COMPLEX NETWORKS, 2021)

What Is Learned in Knowledge Graph Embeddings? - Michael R. Douglas; Michael Simkin; Omri Ben-Eliezer; Tianqi Wu; Peter Chin 001; Trung V. Dang; Andrew Wood (COMPLEX NETWORKS, 2021)

Deep Reinforcement Learning for FlipIt Security Game. - Laura Greige; Peter Chin 001 (COMPLEX NETWORKS, 2021)

Neural Network Optimization with Biologically Inspired Low-Dimensional Manifold Learning. - Hieu Le; Andrew Wood; Sylee Dandekar; Peter Chin 001 (CSCI, 2021)

Corrupting Data to Remove Deceptive Perturbation: Using Preprocessing Method to Improve System Robustness. - Hieu Le; Hans Walker; Dung N. Tran; Peter Chin 001 (CSCI, 2021)

Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis. - Andrew Wood; Moshik Hershcovitch; Daniel G. Waddington; Sarel Cohen; Meredith Wolf; Hongjun Suh; Weiyu Zong; Peter Chin 001 (HPEC, 2021)

Training Many-to-Many Recurrent Neural Networks with Target Propagation. - Peilun Dai; Sang Chin 001 (ICANN (4), 2021)

A Scale Invariant Measure of Flatness for Deep Network Minima. - Akshay Rangamani; Nam H. Nguyen; Abhishek Kumar; Dzung T. Phan; Sang (Peter) Chin; Trac D. Tran (ICASSP, 2021)

How Dense Autoencoders can still Achieve the State-of-the-art in Time-Series Anomaly Detection. - Louis Jensen; Jayme Fosa; Ben Teitelbaum; Peter Chin 001 (ICMLA, 2021)

Mixed Spatio-Temporal Neural Networks on Real-time Prediction of Crimes. - Xiao Zhou; Xiao Wang 028; Gavin Brown 003; Chengchen Wang; Peter Chin 001 (ICMLA, 2021)

PATCHCOMM: Using Commonsense Knowledge to Guide Syntactic Parsers. - Yida Xin; Henry Lieberman; Peter Chin 001 (KR, 2021)

TAK-ML: Applying Machine Learning at the Tactical Edge. - Peter Chin 001; Emily Do; Cody Doucette; Brandon Kalashian; David C. Last; Nathan Lenz; Edward Lu; Devon Minor; Elias Noyes; Colleen T. Rock; Nathaniel Soule; Nicholas Walczak; et al. (MILCOM, 2021)

Revealing and Protecting Labels in Distributed Training. - Trung Dang 002; Om Thakkar 001; Swaroop Ramaswamy; Rajiv Mathews; Peter Chin 001; Françoise Beaufays (NeurIPS, 2021)

Revisiting the Prepositional-Phrase Attachment Problem Using Explicit Commonsense Knowledge. - Yida Xin; Henry Lieberman; Peter Chin 001 (CoRR, 2021)

Substitutional Neural Image Compression. - Xiao Wang 028; Wei Jiang 001; Wei Wang 311; Shan Liu 001; Brian Kulis; Peter Chin 001 (CoRR, 2021)

Application of Seq2Seq Models on Code Correction. - Shan Huang; Xiao Zhou; Sang Chin 001 (Frontiers Artif. Intell., 2021)

Collusion Detection in Team-Based Multiplayer Games. - Laura Greige; Fernando De Mesentier Silva; Meredith Trotter; Chris Lawrence; Peter Chin 001; Dilip Varadarajan (AAAI Spring Symposium: MAKE, 2022)

A Study on Self-Supervised Object Detection Pretraining. - Trung Dang 002; Simon Kornblith; Huy Thong Nguyen; Peter Chin 001; Maryam Khademi (ECCV Workshops (4), 2022)

Semi-supervised Adversarial Text Generation based on Seq2Seq models. - Hieu Le; Dieu-Thu Le; Verena Weber; Chris Church; Kay Rottmann; Melanie Bradford; Peter Chin 001 (EMNLP (Industry Track), 2022)

Towards Fast Crash-Consistent Cluster Checkpointing. - Andrew Wood; Moshik Hershcovitch; Ilias Ennmouri; Weiyu Zong; Saurav Chennuri; Sarel Cohen; Swaminathan Sundararaman; Daniel G. Waddington; Sang (Peter) Chin (HPEC, 2022)

Training Robust Zero-Shot Voice Conversion Models with Self-Supervised Features. - Trung Dang 002; Dung N. Tran; Peter Chin 001; Kazuhito Koishida (ICASSP, 2022)

A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter IT. - Trung Dang 002; Om Thakkar 001; Swaroop Ramaswamy; Rajiv Mathews; Peter Chin 001; Françoise Beaufays (ICASSP, 2022)

Biologically Plausible Complex-Valued Neural Networks and Model Optimization. - Ryan Yu; Andrew Wood; Sarel Cohen; Moshik Hershcovitch; Daniel G. Waddington; Peter Chin 001 (AIAI (1), 2022)

Substitutional Neural Image Compression. - Xiao Wang 028; Ding Ding 004; Wei Jiang 001; Wei Wang 311; Xiaozhong Xu; Shan Liu 001; Brian Kulis; Peter Chin 001 (PCS, 2022)

Non-Volatile Memory Accelerated Posterior Estimation. - Andrew Wood; Moshik Hershcovitch; Daniel G. Waddington; Sarel Cohen; Peter Chin 001 (CoRR, 2022)

Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach. - Hieu Le; Taufiq Husada Daryanto; Fabian Zhafransyah; Derry Wijaya; Elizabeth Coppock; Sang Chin 001 (CoRR, 2022)

A Multi-scale Graph Signature for Persistence Diagrams based on Return Probabilities of Random Walks. - Chau Pham 001; Trung Dang 002; Peter Chin 001 (CoRR, 2022)

Deep Distance Sensitivity Oracles. - Davin Jeong; Chau Pham 001; Arnav Bhakta; Sarel Cohen; Maximilian Katzmann; Tobias Friedrich 001; Sang (Peter) Chin (CoRR, 2022)

cs-net: structural approach to time-series forecasting for high-dimensional feature space data with limited observations. - Weiyu Zong; Mingqian Feng; Griffin Heyrich; Peter Chin 001 (CoRR, 2022)

Learned Approximate Distance Labels for Graphs. - Ikeoluwa Abioye; Allison Gunby-Mann; Xu Wang; Sarel Cohen; Peter Chin 001 (COMPLEX NETWORKS (1), 2023)

Improving Low-Latency Mono-Channel Speech Enhancement by Compensation Windows in STFT Analysis. - Minh N. Bui; Dung N. Tran; Kazuhito Koishida; Trac D. Tran; Peter Chin 001 (COMPLEX NETWORKS (1), 2023)

Deep Distance Sensitivity Oracles. - Davin Jeong; Allison Gunby-Mann; Sarel Cohen; Maximilian Katzmann; Chau Pham 001; Arnav Bhakta; Tobias Friedrich 001; Peter Chin 001 (COMPLEX NETWORKS (1), 2023)

ANEDA: Adaptable Node Embeddings for Shortest Path Distance Approximation. - Frank Pacini; Allison Gunby-Mann; Sarel Cohen; Peter Chin 001 (HPEC, 2023)

Adversarial Transformer Language Models for Contextual Commonsense Inference. - Pedro Colon-Hernandez; Henry Lieberman; Yida Xin; Claire Yin; Cynthia Breazeal; Peter Chin 001 (CoRR, 2023)

On the Transition from Neural Representation to Symbolic Knowledge. - Junyan Cheng; Peter Chin 001 (CoRR, 2023)

Generalizing Topological Graph Neural Networks with Paths. - Quang Truong; Peter Chin 001 (CoRR, 2023)

Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes. - Quang Truong; Peter Chin 001 (AAAI, 2024)

Graphical Learning Optimization and Dimensionality Reduction with Geometric Multi-Resolution Analysis. - Felicia Schenkelberg; Allison Gunby-Mann; Emma Graham; Shuoxuan Li; Peter Chin 001 (HPEC, 2024)

Detecting Continuous Gravitational Waves Using Generated Training Data. - Judith Herrmann; Raphael Kunert; Ron Hachmon; Aviv Markus; Allison Gunby-Mann; Sarel Cohen; Tobias Friedrich 001; Peter Chin 001 (ICASSP, 2024)

SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series. - Junyan Cheng; Peter Chin 001 (ICLR, 2024)

Bridging Neural and Symbolic Representations with Transitional Dictionary Learning. - Junyan Cheng; Peter Chin 001 (ICLR, 2024)

Safe multi-agent reinforcement learning for bimanual dexterous manipulation. - Weishu Zhan; Peter Chin 001 (IROS, 2024)

Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals. - Xiao Zhou; Akshara Rao Balachandra; Michael F. Romano; Sang Peter Chin; Rhoda Au; Vijaya B. Kolachalama (IEEE Access, 2024)

TopoX: A Suite of Python Packages for Machine Learning on Topological Domains. - Mustafa Hajij; Mathilde Papillon; Florian Frantzen; Jens Agerberg; Ibrahem AlJabea; Rubén Ballester; Claudio Battiloro; Guillermo Bernárdez; Tolga Birdal; Aiden Brent; Peter Chin 001; Sergio Escalera; et al. (CoRR, 2024)

Lossless and Near-Lossless Compression for Foundation Models. - Moshik Hershcovitch; Leshem Choshen; Andrew Wood; Ilias Enmouri; Peter Chin 001; Swaminathan Sundararaman; Danny Harnik (CoRR, 2024)

Tree Search for Simultaneous Move Games via Equilibrium Approximation. - Ryan Yu; Alex Olshevsky; Peter Chin 001 (CoRR, 2024)

AAPM: Large Language Model Agent-based Asset Pricing Models. - Junyan Cheng; Peter Chin 001 (CoRR, 2024)

Can Language Models Take A Hint? Prompting for Controllable Contextualized Commonsense Inference. - Pedro Colon-Hernandez; Nanxi Liu; Chelsea Joe; Sang (Peter) Chin; Claire Yin; Henry Lieberman; Yida Xin; Cynthia Breazeal (CoRR, 2024)

Reward-RAG: Enhancing RAG with Reward Driven Supervision. - Thang Nguyen; Peter Chin 001; Yu-Wing Tai (CoRR, 2024)

ZipNN: Lossless Compression for AI Models. - Moshik Hershcovitch; Andrew Wood; Leshem Choshen; Guy Girmonsky; Roy Leibovitz; Ilias Ennmouri; Michal Malka; Peter Chin 001; Swaminathan Sundararaman; Danny Harnik (CoRR, 2024)

Degree Matrix Comparison for Graph Alignment. - Ashley Wang; Peter Chin 001 (CoRR, 2024)

Explore Reinforced: Equilibrium Approximation with Reinforcement Learning. - Ryan Yu; Mateusz Nowak 002; Qintong Xie; Michelle Yilin Feng; Peter Chin 001 (CoRR, 2024)

Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense. - Aditya Vikram Singh; Ethan Rathbun; Emma Graham; Lisa Oakley; Simona Boboila; Peter Chin 001; Alina Oprea (AAMAS, 2025)

Teaching Wav2Vec2 the Language of the Brain. - Tobias Fiedler; Leon Hermann; Florian Müller 018; Sarel Cohen; Sang (Peter) Chin; Tobias Friedrich 001; Eilon Vaadia (CoRR, 2025)

VoD-3DGS: View-opacity-Dependent 3D Gaussian Splatting. - Mateusz Nowak 002; Wojciech Jarosz; Sang (Peter) Chin (CoRR, 2025)

Advancing Differentiable Economics: A Neural Network Framework for Revenue-Maximizing Combinatorial Auction Mechanisms. - Mai Pham; Vikrant Vaze; Peter Chin 001 (CoRR, 2025)

Quantitative Resilience Modeling for Autonomous Cyber Defense. - Xavier Cadet; Simona Boboila; Edward Koh; Peter Chin 001; Alina Oprea (CoRR, 2025)

Ricci Matrix Comparison for Graph Alignment: A DMC Variation. - Ashley Wang; Peter Chin 001 (CoRR, 2025)

MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning. - Thang Nguyen; Peter Chin 001; Yu-Wing Tai (CoRR, 2025)