Unifying Bilateral Filtering and Adversarial Training for Robust Neural Networks. - Neale Ratzlaff; Fuxin Li (CoRR, 2018)

HyperGAN: A Generative Model for Diverse, Performant Neural Networks. - Neale Ratzlaff; Fuxin Li (ICML, 2019)

Implicit Generative Modeling for Efficient Exploration. - Neale Ratzlaff; Qinxun Bai; Fuxin Li; Wei Xu 017 (ICML, 2020)

Avoiding Side Effects in Complex Environments. - Alexander Matt Turner; Neale Ratzlaff; Prasad Tadepalli (NeurIPS, 2020)

Generative Particle Variational Inference via Estimation of Functional Gradients. - Neale Ratzlaff; Qinxun Bai; Fuxin Li; Wei Xu 017 (ICML, 2021)

Contrastive Identification of Covariate Shift in Image Data. - Matthew L. Olson; Thuy-Vy Nguyen; Gaurav Dixit; Neale Ratzlaff; Weng-Keen Wong; Minsuk Kahng (IEEE VIS (Short Papers), 2021)

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)

Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations. - Neale Ratzlaff; Matthew Lyle Olson; Musashi Hinck; Shao-Yen Tseng; Vasudev Lal; Phillip Howard (CoRR, 2024)

Debias your Large Multi-Modal Model at Test-Time with Non-Contrastive Visual Attribute Steering. - Neale Ratzlaff; Matthew Lyle Olson; Musashi Hinck; Estelle Aflalo; Shao-Yen Tseng; Vasudev Lal; Phillip Howard (CoRR, 2024)

Steering Large Language Models to Evaluate and Amplify Creativity. - Matthew Lyle Olson; Neale Ratzlaff; Musashi Hinck; Shao-Yen Tseng; Vasudev Lal (CoRR, 2024)

Training-Free Mitigation of Language Reasoning Degradation After Multimodal Instruction Tuning. - Neale Ratzlaff; Man Luo; Xin Su 008; Vasudev Lal; Phillip Howard (AAAI Spring Symposia, 2025)

Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders. - Matthew Lyle Olson; Musashi Hinck; Neale Ratzlaff; Changbai Li; Phillip Howard; Vasudev Lal; Shao-Yen Tseng (CVPR Workshops, 2025)

Semantic Specialization in MoE Appears with Scale: A Study of DeepSeek R1 Expert Specialization. - Matthew Lyle Olson; Neale Ratzlaff; Musashi Hinck; Man Luo; Sungduk Yu; Chendi Xue; Vasudev Lal (CoRR, 2025)

Probing the Representational Power of Sparse Autoencoders in Vision Models. - Matthew Lyle Olson; Musashi Hinck; Neale Ratzlaff; Changbai Li; Phillip Howard; Vasudev Lal; Shao-Yen Tseng (CoRR, 2025)