Johns Hopkins researchers, including several affiliated with the Johns Hopkins Data Science and AI Institute, will present their research in poster sessions and workshops during the 2025 Conference on Neural Information Processing Systems (NeurIPS), to be held Tuesday, Dec. 2, through Sunday, Dec. 7, in San Diego.
NeurIPS is an interdisciplinary annual event that highlights advancements in machine learning, artificial intelligence, and computational neuroscience through talks, demonstrations, symposia, and oral and poster presentations. The conference is organized by the Neural Information Processing Systems Foundation.
Johns Hopkins-affiliated researchers will present the following papers:
Spotlight Posters
AutoToM: Scaling Model-based Mental Inference via Automated Agent Modeling
Zhining Zhang, Chuanyang Jin, Mung Yao Jia, Shunchi Zhang, Tianmin Shu
ESCA: Contextualizing Embodied Agents via Scene-Graph Generation
Jiani Huang, Mayank Keoliya, Matthew Kuo, Neelay Velingker, Amish Sethi, JungHo Jung, Ser-Nam Lim, Ziyang Li, Mayur Naik
Nonlinear Laplacians: Tunable principal component analysis under directional prior information
Yuxin Ma, Dmitriy Kunisky
On Transferring Transferability: Towards a Theory for Size Generalization
Eitan Levin, Yuxin Ma, Mateo Diaz, Soledad Villar
Personalized Decision Modeling: Utility Optimization or Textualized-Symbolic Reasoning
Yibo Zhao, Yang Zhao, Hongru Du, Hao Frank Yang
Towards Physics-informed Visual-Spatial Intelligence with Human Priors: An Autonomous Driving Pilot Study
Guanlin (Frank) Wu, Boyan Su, Yang Zhao, Pu Wang, Yichen Lin, Hao Frank Yang
Posters
A cautionary tale on integrating studies with disparate outcome measures for causal inference
Harsh Parikh, Trang Quynh Nguyen, Elizabeth A. Stuart, Kara E. Rudolph, Caleb H. Miles
A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances
Michael Dinitz, Chenglin Fan, Jingcheng Liu, Jalaj Upadhyay, Zongrui Zou
Are Pixel-Wise Metrics Reliable for Sparse-View Computed Tomography Reconstruction?
Tianyu Lin, Xinran Li, Chuntung Zhuang, Qi Chen, Yuanhao Cai, Kai Ding, Alan Yuille, Zongwei Zhou
Beyond Scores: Proximal Diffusion Models
Zhenghan Fang, Mateo Diaz, Samuel Buchanan, Jeremias Sulam
Characterization and Learning of Causal Graphs from Hard Interventions
Zihan Zhou, Muhammed Qasim Elahi, Murat Kocaoglu
Conformal Linguistic Calibration: Trading-off between Factuality and Specificity
Zhengping Jiang, Anqi Liu, Benjamin Van Durme
Constrained Entropic Unlearning: A Primal-Dual Framework for Large Language Models
Taha Entesari, Arman Hatami, Rinat Khaziev, Anil Ramakrishna, Mahyar Fazlyab
Differentiable Constraint-Based Causal Discovery
Jincheng Zhou, Mengbo Wang, Anqi He, Yumeng Zhou, Hessam Olya, Murat Kocaoglu, Bruno Ribeiro
DRIFT: Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents
Hao Li, Xiaogeng Liu, Hung-Chun Chiu, Dianqi Li, Ning Zhang, Chaowei Xiao
Extragradient Method for (L0, L1)-Lipschitz Variational Inequalities
Sayantan Choudhury, Nicolas Loizou
Galactification: painting galaxies onto dark matter only simulations using a transformer-based model
Shivam Pandey, Christopher C. Lovell, Chirag Modi, Benjamin Dan Wandelt
How to Auto-optimize Prompts for Domain Tasks? Adaptive Prompting and Reasoning through Evolutionary Domain Knowledge Adaptation
Yang Zhao, Pu Wang, Hao Frank Yang
Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis
Sihan Zeng, Benjamin Patrick Evans, Sujay Bhatt, Leo Ardon, Sumitra Ganesh, Alec Koppel
Monitoring Risks in Test-Time Adaptation
Mona Schirmer, Metod Jazbec, Christian Naesseth, Eric Nalisnick
Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
TaeHo Yoon, Sayantan Choudhury, Nicolas Loizou
OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions
Yuanhao Cai, He Zhang, Xi Chen, Jinbo Xing, Yiwei Hu, Yuqian Zhou, Kai Zhang, Zhifei Zhang, Soo Ye Kim, Tianyu Wang, Yulun Zhang, Xiaokang Yang, Zhe Lin, Alan Yuille
On the Emergence of Linear Analogies in Word Embeddings
Daniel James Korchinski, Dhruva Karkada, Yasaman Bahri, Matthieu Wyart
Optical Coherence Tomography Harmonization with Anatomy-Guided Latent Metric Schrödinger Bridges
Shuwen Wei, Samuel W. Remedios, Blake E. Dewey, Zhangxing Bian, Shimeng Wang, Junyu Chen, Bruno Michel Jedynak, shiv saidha, Peter A. Calabresi, Aaron Carass, Jerry L Prince
PanTS: The Pancreatic Tumor Segmentation Dataset
Wenxuan Li, Xinze Zhou, Qi Chen, Tianyu Lin, Pedro R. A. S. Bassi, Xiaoxi Chen, Chen Ye, Zheren Zhu, Kai Ding, Heng Li, Kang Wang, Yang Yang, Yucheng Tang, Daguang Xu, Alan Yuille, Zongwei Zhou
SAM2Flow: Interactive Optical Flow Estimation with Dual Memory for in vivo Microcirculation Analysis
Luojie Huang, Ryan Zhang, Marisa Morakis, Michaela Taylor-Williams, Gregory McKay, Nicholas Durr
Synthesizing Photorealistic and Dynamic Urban Environments for Multimodal Robot Navigation and Collaboration
Yan Zhuang, Jiawei Ren, Xiaokang Ye, Jianzhi Shen, Ruixuan Zhang, Tianai Yue, Muhammad Faayez, Xuhong He, Xiyan Zhang, Ziqiao Ma, Lianhui Qin, Zhiting Hu, Tianmin Shu
SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning
Wufei Ma, Yu-Cheng Chou, Qihao Liu, Xingrui Wang, Celso M de Melo, Jianwen Xie, Alan Yuille
Vision‑Language‑Vision Auto‑Encoder: Scalable Knowledge Distillation from Diffusion Models
Tiezheng Zhang, Yitong Li, Yu-Cheng Chou, Jieneng Chen, Alan Yuille, Chen Wei, Junfei Xiao
Visual Jenga: Discovering Object Dependencies via Counterfactual Inpainting
Anand Bhattad, Konpat Preechakul, Alexei A. Efros
When Does Curriculum Learning Help? A Theoretical Perspective
Kaibo Zhang, Yunjuan Wang, Raman Arora
Whitened Score Diffusion: A Structured Prior for Imaging Inverse Problems
Jeffrey Alido, Tongyu Li, Yu Sun, and Lei Tian
Workshop Papers
AttentiveGRUAE: An Attention-Based GRU Autoencoder for Temporal Clustering and Behavioral Characterization of Depression from Wearable Data
Nidhi Soley, Vishal M. Patel, and Casey O. Taylor
Causal Masking on Spatial Data: An Information-Theoretic Case for Learning Spatial Datasets with Unimodal Language Models
Jared Junkin, Samuel Nathanson
Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials
Edward W. Staley, Tom Arbaugh, Michael Pekala, Alex New, Christopher D. Stiles, Nam Q. Le, Gregory Bassen, Wyatt Bunstine, Tyrel McQueen
Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees
Bo Tang, Elias B. Khalil, Ján Drgoňa
Migration as a probe: A generalizable benchmark framework for specialist vs. generalist machine-learned force fields
Yi Cao, Paulette Clancy
Re-envisioning Euclid Galaxy Morphology: Identifying and Interpreting Features with Sparse Autoencoders
John F. Wu, Michael Walmsley
Solving Bi-Level Reinforcement Learning: A Regularized Actor-Critic Algorithm with Finite-Sample Analysis
Sihan Zeng, Sujay Bhatt, Sumitra Ganesh, Alec Koppel
The Explore-Exploit Tradeoff Redefined: Balancing Regret and Treatment Effects in Contextual Bandits
Alec Koppel, Sujay Bhatt, Sihan Zeng, Sumitra Ganesh
The Platonic Universe: Do Foundation Models See the Same Sky?
Kshitij Duraphe, Michael J. Smith, Shashwat Sourav, John F. Wu
