Planning in Factored Action Spaces with Symbolic Dynamic Programming. - Aswin Raghavan; Saket Joshi; Alan Fern; Prasad Tadepalli; Roni Khardon (AAAI, 2012)

Relational Markov Decision Processes: Promise and Prospects. - Saket Joshi; Roni Khardon; Prasad Tadepalli; Alan Fern; Aswin Raghavan (StarAI@AAAI, 2013)

Symbolic Opportunistic Policy Iteration for Factored-Action MDPs. - Aswin Raghavan; Roni Khardon; Alan Fern; Prasad Tadepalli (NIPS, 2013)

Solving Relational MDPs with Exogenous Events and Additive Rewards. - Saket Joshi; Roni Khardon; Prasad Tadepalli; Aswin Raghavan; Alan Fern (ECML/PKDD (1), 2013)

Memory-Effcient Symbolic Online Planning for Factored MDPs. - Aswin Raghavan; Roni Khardon; Prasad Tadepalli; Alan Fern (UAI, 2015)

Hindsight Optimization for Hybrid State and Action MDPs. - Aswin Raghavan; Scott Sanner; Roni Khardon; Prasad Tadepalli; Alan Fern (AAAI, 2017)

Low Precision Neural Networks using Subband Decomposition. - Sek M. Chai; Aswin Raghavan; David C. Zhang; Mohamed R. Amer; Timothy J. Shields (CoRR, 2017)

GPU Activity Prediction using Representation Learning. - Aswin Raghavan; Mohamed R. Amer; Timothy J. Shields; David C. Zhang; Sek M. Chai (CoRR, 2017)

BitNet: Bit-Regularized Deep Neural Networks. - Aswin Raghavan; Mohamed R. Amer; Sek M. Chai (CoRR, 2017)

Event Prediction in Processors Using Deep Temporal Models. - C. D. Tharindu Mathew; Aswin Raghavan; Sek Chai (EMC2@ASPLOS, 2018)

Emergency Response Optimization using Online Hybrid Planning. - Durga Harish Dayapule; Aswin Raghavan; Prasad Tadepalli; Alan Fern (IJCAI, 2018)

Aesop: A Visual Storytelling Platform for Conversational AI. - Tim Meo; Aswin Raghavan; David A. Salter; Alex Tozzo; Amir Tamrakar; Mohamed R. Amer (IJCAI, 2018)

Detecting Zero-day Controller Hijacking Attacks on the Power-Grid with Enhanced Deep Learning. - Zecheng He; Aswin Raghavan; Sek M. Chai; Ruby B. Lee (CoRR, 2018)

Generalized Ternary Connect: End-to-End Learning and Compression of Multiplication-Free Deep Neural Networks. - Samyak Parajuli; Aswin Raghavan; Sek M. Chai (CoRR, 2018)

Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning. - Zecheng He; Aswin Raghavan; Guangyuan Hu; Sek M. Chai; Ruby B. Lee (TrustCom/BigDataSE, 2019)

Aesop: A visual storytelling platform for conversational AI and common sense grounding. - Timothy J. Meo; Chris Kim; Aswin Raghavan; Alex Tozzo; David A. Salter; Amir Tamrakar; Mohamed R. Amer (AI Commun., 2019)

Generative Memory for Lifelong Reinforcement Learning. - Aswin Raghavan; Jesse Hostetler; Sek M. Chai (CoRR, 2019)

Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition, and Selective Transfer. - Aswin Raghavan; Jesse Hostetler; Indranil Sur; Abrar Rahman; Ajay Divakaran (CoRR, 2020)

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. - Indranil Sur; Zachary Daniels; Abrar Rahman; Kamil Faber; Gianmarco J. Gallardo; Tyler L. Hayes; Cameron E. Taylor; Mustafa Burak Gurbuz; James Seale Smith; Sahana Pramod Joshi; Nathalie Japkowicz; Michael Baron; et al. (AIMLSystems, 2022)

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. - Zachary Alan Daniels; Aswin Raghavan; Jesse Hostetler; Abrar Rahman; Indranil Sur; Michael R. Piacentino; Ajay Divakaran; Roberto Corizzo; Kamil Faber; Nathalie Japkowicz; Michael Baron; James Seale Smith; et al. (CoLLAs, 2022)

Real-time Hyper-Dimensional Reconfiguration at the Edge using Hardware Accelerators. - Indhumathi Kandaswamy; Saurabh Farkya; Zachary Daniels; Gooitzen van der Wal; Aswin Raghavan; Yuzheng Zhang; Jun Hu; Michael Lomnitz; Michael A. Isnardi; David C. Zhang; Michael R. Piacentino (CVPR Workshops, 2022)

Saccade Mechanisms for Image Classification, Object Detection and Tracking. - Saurabh Farkya; Zachary Daniels; Aswin Nadamuni Raghavan; David C. Zhang; Michael R. Piacentino (CoRR, 2022)

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. - Zachary Daniels; Aswin Raghavan; Jesse Hostetler; Abrar Rahman; Indranil Sur; Michael R. Piacentino; Ajay Divakaran (CoRR, 2022)

Low-power In-pixel Computing with Current-modulated Switched Capacitors. - David C. Zhang; Gooitzen van der Wal; Saurabh Farkya; Thomas Senko; Aswin Raghavan; Michael A. Isnardi; Michael R. Piacentino (CoRR, 2022)

Efficient Model Adaptation for Continual Learning at the Edge. - Zachary A. Daniels; Jun Hu; Michael Lomnitz; Phil Miller; Aswin Raghavan; Joe Zhang; Michael R. Piacentino; David C. Zhang (CoRR, 2023)

Enhancing Multi-Agent Coordination through Common Operating Picture Integration. - Peihong Yu; Bhoram Lee; Aswin Raghavan; Supun Samarasekera; Pratap Tokekar; James Zachary Hare (CoRR, 2023)

Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training. - Saurabh Farkya; Aswin Raghavan; Avi Ziskind (CoRR, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)

Tools Identification By On-Board Adaptation of Vision-and-Language Models. - Jun Hu; Phil Miller; Michael Lomnitz; Saurabh Farkya; Emre Yilmaz; Aswin Raghavan; David C. Zhang; Michael R. Piacentino (AAAI, 2024)

Data-Driven Pixel Control: Challenges and Prospects. - Saurabh Farkya; Zachary Alan Daniels; Aswin Raghavan; Gooitzen van der Wal; Michael A. Isnardi; Michael R. Piacentino; David C. Zhang (DDDAS/Infosymbiotics, 2024)

Data-Driven Distributed Common Operational Picture from Heterogeneous Platforms using Multi-Agent Reinforcement Learning. - Indranil Sur; Aswin Raghavan; Abrar Rahman; James Zachary Hare; Daniel N. Cassenti; Carl E. Busart (CoRR, 2024)

Noise-Tolerant Coreset-Based Class Incremental Continual Learning. - Edison Mucllari; Aswin Raghavan; Zachary Alan Daniels (CoRR, 2025)