Discrete Cosine Transform Spectral Pooling Layers for Convolutional Neural Networks. - James Seale Smith; Bogdan M. Wilamowski (ICAISC (1), 2018)

Unsupervised Continual Learning and Self-Taught Associative Memory Hierarchies. - James Seale Smith; Seth Baer; Zsolt Kira; Constantine Dovrolis (CoRR, 2019)

DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization. - Bo Wu 024; James Seale Smith; Bogdan M. Wilamowski; R. M. Nelms (J. Vis., 2019)

Neural Network Training With Levenberg-Marquardt and Adaptable Weight Compression. - James Seale Smith; Bo Wu 024; Bogdan M. Wilamowski (IEEE Trans. Neural Networks Learn. Syst., 2019)

Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning. - James Seale Smith; Yen-Chang Hsu; Jonathan Balloch; Yilin Shen; Hongxia Jin; Zsolt Kira (ICCV, 2021)

Unsupervised Progressive Learning and the STAM Architecture. - James Seale Smith; Cameron E. Taylor; Seth Baer; Constantine Dovrolis (IJCAI, 2021)

Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer. - James Seale Smith; Jonathan Balloch; Yen-Chang Hsu; Zsolt Kira (IJCNN, 2021)

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)

Incremental Learning with Differentiable Architecture and Forgetting Search. - James Seale Smith; Zachary Seymour; Han-Pang Chiu (IJCNN, 2022)

A Closer Look at Knowledge Distillation with Features, Logits, and Gradients. - Yen-Chang Hsu; James Seale Smith; Yilin Shen; Zsolt Kira; Hongxia Jin (CoRR, 2022)

A Closer Look at Rehearsal-Free Continual Learning. - James Seale Smith; Junjiao Tian; Yen-Chang Hsu; Zsolt Kira (CoRR, 2022)

Lifelong Wandering: A realistic few-shot online continual learning setting. - Mayank Lunayach; James Seale Smith; Zsolt Kira (CoRR, 2022)

FedFOR: Stateless Heterogeneous Federated Learning with First-Order Regularization. - Junjiao Tian; James Seale Smith; Zsolt Kira (CoRR, 2022)

On the Transferability of Visual Features in Generalized Zero-Shot Learning. - Paola Cascante-Bonilla; Leonid Karlinsky; James Seale Smith; Yanjun Qi; Vicente Ordonez (CoRR, 2022)

Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. - Martin Mundt; Keiland W. Cooper; Devendra Singh Dhami; Adèle H. Ribeiro; James Seale Smith; Alexis Bellot; Tyler L. Hayes (AAAI Bridge Program, 2023)

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning. - James Seale Smith; Paola Cascante-Bonilla; Assaf Arbelle; Donghyun Kim 006; Rameswar Panda; David D. Cox; Diyi Yang; Zsolt Kira; Rogério Feris; Leonid Karlinsky (CVPR, 2023)

CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning. - James Seale Smith; Leonid Karlinsky; Vyshnavi Gutta; Paola Cascante-Bonilla; Donghyun Kim 006; Assaf Arbelle; Rameswar Panda; Rogério Feris; Zsolt Kira (CVPR, 2023)

A Closer Look at Rehearsal-Free Continual Learning. - James Seale Smith; Junjiao Tian; Shaunak Halbe; Yen-Chang Hsu; Zsolt Kira (CVPR Workshops, 2023)

Going Beyond Nouns With Vision & Language Models Using Synthetic Data. - Paola Cascante-Bonilla; Khaled Shehada; James Seale Smith; Sivan Doveh; Donghyun Kim 006; Rameswar Panda; Gül Varol; Aude Oliva; Vicente Ordonez; Rogério Feris; Leonid Karlinsky (ICCV, 2023)

Fast Trainable Projection for Robust Fine-tuning. - Junjiao Tian; Yen-Cheng Liu; James Seale Smith; Zsolt Kira (NeurIPS, 2023)

HePCo: Data-Free Heterogeneous Prompt Consolidation for Continual Federated Learning. - Shaunak Halbe; James Seale Smith; Junjiao Tian; Zsolt Kira (CoRR, 2023)

Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters. - James Seale Smith; Yen-Chang Hsu; Zsolt Kira; Yilin Shen; Hongxia Jin (CVPR Workshops, 2024)

Adaptive Memory Replay for Continual Learning. - James Seale Smith; Lazar Valkov; Shaunak Halbe; Vyshnavi Gutta; Rogério Feris; Zsolt Kira; Leonid Karlinsky (CVPR Workshops, 2024)

SLiM: Speculative Decoding with Hypothesis Reduction. - Chi-Heng Lin; Shikhar Tuli; James Seale Smith; Yen-Chang Hsu; Yilin Shen; Hongxia Jin (NAACL-HLT (Findings), 2024)

Grounding Descriptions in Images informs Zero-Shot Visual Recognition. - Shaunak Halbe; Junjiao Tian; K. J. Joseph; James Seale Smith; Katherine Stevo; Vineeth N. Balasubramanian; Zsolt Kira (CoRR, 2024)

Continual Adaptation of Vision Transformers for Federated Learning. - Shaunak Halbe; James Seale Smith; Junjiao Tian; Zsolt Kira (Trans. Mach. Learn. Res., 2024)

Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA. - James Seale Smith; Yen-Chang Hsu; Lingyu Zhang; Ting Hua; Zsolt Kira; Yilin Shen; Hongxia Jin (Trans. Mach. Learn. Res., 2024)

Lifelong Machine Learning without Lifelong Data Retention. - James Seale Smith (2024)

MoDeGPT: Modular Decomposition for Large Language Model Compression. - Chi-Heng Lin; Shangqian Gao; James Seale Smith; Abhishek Patel; Shikhar Tuli; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (ICLR, 2025)

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing. - James Seale Smith; Chi-Heng Lin; Shikhar Tuli; Haris Jeelani; Shangqian Gao; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (NAACL (Long Papers), 2025)