Jiralerspong, Thomas

11 publications

ICLR 2025 Expressivity of Neural Networks with Random Weights and Learned Biases Ezekiel Williams, Alexandre Payeur, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Matthew G Perich, Luca Mazzucato, Guillaume Lajoie

ICLRW 2025 Shaping Inductive Bias in Diffusion Models Through Frequency-Based Noise Control Thomas Jiralerspong, Berton Earnshaw, Jason Hartford, Yoshua Bengio, Luca Scimeca

ICML 2025 Towards a Formal Theory of Representational Compositionality Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie

ICLRW 2024 Efficient Causal Graph Discovery Using Large Language Models Thomas Jiralerspong, Xiaoyin Chen, Yash More, Vedant Shah, Yoshua Bengio

ICMLW 2024 Expressivity of Neural Networks with Fixed Weights and Learned Biases Ezekiel Williams, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Alexandre Payeur, Matthew G Perich, Luca Mazzucato, Guillaume Lajoie

NeurIPSW 2024 General Causal Imputation via Synthetic Interventions Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel

NeurIPSW 2024 Geometric Signatures of Compositionality Across a Language Model’s Lifetime Jin Hwa Lee, Thomas Jiralerspong, Lei Yu, Emily Cheng

NeurIPSW 2024 Geometric Signatures of Compositionality in Language Models Thomas Jiralerspong, Jin Hwa Lee, Lei Yu, Emily Cheng

NeurIPS 2023 Contrastive Retrospection: Honing in on Critical Steps for Rapid Learning and Generalization in RL Chen Sun, Wannan Yang, Thomas Jiralerspong, Dane Malenfant, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake Richards

NeurIPSW 2023 Forecaster: Towards Temporally Abstract Tree-Search Planning from Pixels Thomas Jiralerspong, Flemming Kondrup, Doina Precup, Khimya Khetarpal

AAAI 2023 Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement Learning Flemming Kondrup, Thomas Jiralerspong, Elaine Lau, Nathan de Lara, Jacob Shkrob, My Duc Tran, Doina Precup, Sumana Basu