TMLR

Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization

Han Guo, Ramtin Hosseini, Ruiyi Zhang, Sai Ashish Somayajula, Ranak Roy Chowdhury, Rajesh K. Gupta, Pengtao Xie

Comments Published in Transactions on Machine Learning Research (TMLR)

Diffusion Models with Deterministic Normalizing Flow Priors

Mohsen Zand, Ali Etemad, Michael Greenspan

Comments 17 pages, 7 figures, Published in Transactions on Machine Learning Research (TMLR)

Journal ref https://openreview.net/pdf?id=ACMNVwcR6v, Transactions on Machine Learning Research (TMLR), 2024

Characterizing the Convergence of Game Dynamics via Potentialness

Martin Bichler, Davide Legacci, Panayotis Mertikopoulos, Matthias Oberlechner, Bary Pradelski

Journal ref Transactions on Machine Learning Research (TMLR), 2025

Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning

Amin Banayeeanzade, Mahdi Soltanolkotabi, Mohammad Rostami

Comments TMLR camera-ready version

Enhancing Maritime Trajectory Forecasting via H3 Index and Causal Language Modelling (CLM)

Nicolas Drapier, Aladine Chetouani, Aurélien Chateigner

Comments 28 pages, 18 figures

Journal ref Transactions on Machine Learning Research (2025)

Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization

Sara Venturini, Marianna de Santis, Jordan Patracone, Francesco Rinaldi, Saverio Salzo, Martin Schmidt

Journal ref Transactions on Machine Learning Research Journal, 2025

Neuron-based explanations of neural networks sacrifice completeness and interpretability

Nolan Dey, Eric Taylor, Alexander Wong, Bryan Tripp, Graham W. Taylor

Comments TMLR 2025

Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design

Lev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernardez, Olga Zaghen, Simone Scardapane, Pietro Lio

Comments This work has been published in Transactions on Machine Learning Research (TMLR). Please cite the journal version: https://openreview.net/forum?id=8rxtL0kZnX Link to bib: https://jmlr.org/tmlr/papers/bib/8rxtL0kZnX.bib

Journal ref Transactions on Machine Learning Research, 2025

Diffusion on Graph: Augmentation of Graph Structure for Node Classification

Yancheng Wang, Changyu Liu, Yingzhen Yang

Comments Published in Transactions on Machine Learning Research (TMLR) 2025

Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques

Shwai He, Daize Dong, Liang Ding, Ang Li

Comments Transactions on Machine Learning Research (TMLR)

Ensemble and Mixture-of-Experts DeepONets For Operator Learning

Ramansh Sharma, Varun Shankar

Comments Accepted at Transactions of Machine Learning Research (TMLR) 2025

Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations

Akshay Kumar, Jarvis Haupt

Comments tmlr-final-version

SimPLR: A Simple and Plain Transformer for Efficient Object Detection and Segmentation

Duy-Kien Nguyen, Martin R. Oswald, Cees G. M. Snoek

Comments In Proceeding of TMLR'2025

On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective

Tal Alter, Raz Lapid, Moshe Sipper

Comments Accepted at TMLR 2025

A unifying framework for generalised Bayesian online learning in non-stationary environments

Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Alexander Y. Shestopaloff, Kevin Murphy

Comments Published in Transactions on Machine Learning Research (03/2025)

Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision

Pranav Jeevan, Amit Sethi

Comments 12 pages, 2 figures, accepted in TMLR

Visual Privacy Auditing with Diffusion Models

Kristian Schwethelm, Johannes Kaiser, Moritz Knolle, Sarah Lockfisch, Daniel Rueckert, Alexander Ziller

Comments Published in Transactions on Machine Learning Research (TMLR)

Uncertainty in Graph Neural Networks: A Survey

Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu

Comments 14 main pages, 4 figures, 1 table

Journal ref Transactions on Machine Learning Research (11/2024)

State space models can express n-gram languages

Vinoth Nandakumar, Qiang Qu, Peng Mi, Tongliang Liu

Comments Published in "Transactions on Machine Learning Research", 2025

The 2024 Foundation Model Transparency Index

Rishi Bommasani, Kevin Klyman, Sayash Kapoor, Shayne Longpre, Betty Xiong, Nestor Maslej, Percy Liang

Comments Published in TMLR 2025. Project page: https://crfm.stanford.edu/fmti

Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning

Ashka Shah, Adela DePavia, Nathaniel Hudson, Ian Foster, Rick Stevens

Comments TMLR 03/2025

Balanced Mixed-Type Tabular Data Synthesis with Diffusion Models

Zeyu Yang, Han Yu, Peikun Guo, Khadija Zanna, Xiaoxue Yang, Akane Sano

Comments OpenReview: https://openreview.net/forum?id=dvRysCqmYQ

Journal ref Transactions on Machine Learning Research, ISSN 2835-8856 (2025)

HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds

Hejia Geng, Peng Li

Comments Accepted by TMLR

Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings

Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft

Comments Published at TMLR (https://openreview.net/forum?id=mSoDRZXsqj)

Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement

Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu

Comments Accepted to TMLR. Code available at https://github.com/AhaChang/DEFEND

Max-Affine Spline Insights Into Deep Network Pruning

Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Celine Lin, Richard Baraniuk

Comments Accepted by TMLR

A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning

Amadou S. Sangare, Nicolas Dunou, Jhony H. Giraldo, Fragkiskos D. Malliaros

Journal ref Transactions on Machine Learning Research, 2025

Shared Stochastic Gaussian Process Latent Variable Models: A Multi-modal Generative Model for Quasar Spectra

Vidhi Lalchand, Anna-Christina Eilers

Comments Published in TMLR, https://openreview.net/pdf?id=LzmsvRTqaJ. The code for this work is available at: https://github.com/vr308/Quasar-GPLVM

Journal ref Transactions on Machine Learning Research (TMLR), 2025

Unlearning Personal Data from a Single Image

Thomas De Min, Massimiliano Mancini, Stéphane Lathuilière, Subhankar Roy, Elisa Ricci

Comments Published in Transactions on Machine Learning Research (TMLR)

Faster Diffusion via Temporal Attention Decomposition

Haozhe Liu, Wentian Zhang, Jinheng Xie, Francesco Faccio, Mengmeng Xu, Tao Xiang, Mike Zheng Shou, Juan-Manuel Perez-Rua, Jürgen Schmidhuber

Comments Accepted by TMLR: https://openreview.net/forum?id=xXs2GKXPnH