TMLR

Shedding Light on Problems with Hyperbolic Graph Learning

Isay Katsman, Anna Gilbert

Comments Published in TMLR

How Does Code Pretraining Affect Language Model Task Performance?

Jackson Petty, Sjoerd van Steenkiste, Tal Linzen

Journal ref Transactions on Machine Learning Research (January 2025)

Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators

Sanjeev Raja, Ishan Amin, Fabian Pedregosa, Aditi S. Krishnapriyan

Journal ref Transactions on Machine Learning Research, 2025

Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases

Madison Cooley, Varun Shankar, Robert M. Kirby, Shandian Zhe

Comments 37 pages, 21 figures

Journal ref Transactions on Machine Learning Research, 2025, https://openreview.net/forum?id=KqRnsEMYLx

Improving Consistency in Large Language Models through Chain of Guidance

Harsh Raj, Vipul Gupta, Domenic Rosati, Subhabrata Majumdar

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

Single-pass Detection of Jailbreaking Input in Large Language Models

Leyla Naz Candogan, Yongtao Wu, Elias Abad Rocamora, Grigorios G. Chrysos, Volkan Cevher

Comments Accepted in TMLR 2025

Optimizing Estimators of Squared Calibration Errors in Classification

Sebastian G. Gruber, Francis Bach

Comments Published at TMLR, see https://openreview.net/forum?id=BPDVZajOW5

Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems

Krishna Acharya, Varun Vangala, Jingyan Wang, Juba Ziani

Comments This paper has been accepted at TMLR

On Memorization in Diffusion Models

Xiangming Gu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Ye Wang

Comments TMLR 2025

Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability

Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters

Comments TMLR 2025

Comparing the information content of probabilistic representation spaces

Kieran A. Murphy, Sam Dillavou, Dani S. Bassett

Comments TMLR 2025; Code at https://github.com/murphyka/representation-space-info-comparison

Evaluation of Best-of-N Sampling Strategies for Language Model Alignment

Yuki Ichihara, Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe, Mitsuki Sakamoto, Eiji Uchibe

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

Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey

Amer Essakine, Yanqi Cheng, Chun-Wun Cheng, Lipei Zhang, Zhongying Deng, Lei Zhu, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

Journal ref Published in Transactions on Machine Learning Research, 2025

Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning

Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang

Journal ref Transactions on Machine Learning Research, 2025

Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization

Aditya Ranganath, Mukesh Singhal, Roummel Marcia

Comments submitted to TMLR

Robust High-Dimensional Mean Estimation With Low Data Size, an Empirical Study

Cullen Anderson, Jeff M. Phillips

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

Understanding LLM Embeddings for Regression

Eric Tang, Bangding Yang, Xingyou Song

Comments Published in Transactions on Machine Learning Research (TMLR) 2025. Code can be found in https://github.com/google-research/optformer

Metalearning Continual Learning Algorithms

Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

Comments Accepted to TMLR 02/2025. An earlier version of this work titled "Automating Continual Learning" was made available online in 2023

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates

Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis

Comments Accepted version in Transactions on Machine Learning Research (TMLR)

Unsupervised Discovery of Object-Centric Neural Fields

Rundong Luo, Hong-Xing Yu, Jiajun Wu

Comments TMLR 2025

Necessary and Sufficient Watermark for Large Language Models

Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

Comments TMLR 2025

On Space Folds of ReLU Neural Networks

Michal Lewandowski, Hamid Eghbalzadeh, Bernhard Heinzl, Raphael Pisoni, Bernhard A. Moser

Comments Accepted at Transactions on Machine Learning Research (TMLR), 2025

Increasing Both Batch Size and Learning Rate Accelerates Stochastic Gradient Descent

Hikaru Umeda, Hideaki Iiduka

Comments TMLR 2025

Verbalized Machine Learning: Revisiting Machine Learning with Language Models

Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu

Comments Published in Transactions on Machine Learning Research (116 pages, 32 figures, v3: refined the paper structure and added more empirical results)

On the Regularization of Learnable Embeddings for Time Series Forecasting

Luca Butera, Giovanni De Felice, Andrea Cini, Cesare Alippi

Comments Accepted at TMLR

Journal ref L. Butera, G. D. Felice, A. Cini, and C. Alippi. On the regularization of learnable embeddings for time series forecasting. Transactions on Machine Learning Research, 2025. ISSN 2835-8856. URL https://openreview.net/forum?id=F5ALCh3GWG

Explaining Explainability: Recommendations for Effective Use of Concept Activation Vectors

Angus Nicolson, Lisa Schut, J. Alison Noble, Yarin Gal

Comments Accepted by Transactions on Machine Learning Research (02/2025)

Global Convergence Rate of Deep Equilibrium Models with General Activations

Lan V. Truong

Comments Accepted to TMLR

Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks

Piyush Tiwary, Atri Guha, Subhodip Panda, Prathosh A. P

Comments Accepted at Transactions on Machine Learning Research (TMLR)

Maximum Mean Discrepancy on Exponential Windows for Online Change Detection

Florian Kalinke, Marco Heyden, Georg Gntuni, Edouard Fouché, Klemens Böhm

Comments Published in TMLR 02/25

Journal ref Transactions on Machine Learning Research, 2025

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs

Song Wang, Zhen Tan, Yaochen Zhu, Chuxu Zhang, Jundong Li

Comments TMLR 02/2025