Thomas, Valentin

11 publications

NeurIPS 2025 CausalPFN: Amortized Causal Effect Estimation via In-Context Learning Vahid Balazadeh, Hamidreza Kamkari, Valentin Thomas, Junwei Ma, Bingru Li, Jesse C. Cresswell, Rahul Krishnan

NeurIPS 2025 TabDPT: Scaling Tabular Foundation Models on Real Data Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh, Alex Labach, Jesse C. Cresswell, Keyvan Golestan, Guangwei Yu, Anthony L. Caterini, Maksims Volkovs

NeurIPS 2024 Retrieval & Fine-Tuning for In-Context Tabular Models Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony Caterini

ICMLW 2024 Retrieval & Fine-Tuning for In-Context Tabular Models Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini

TMLR 2023 Bridging the Gap Between Target Networks and Functional Regularization Alexandre Piché, Valentin Thomas, Joseph Marino, Rafael Pardinas, Gian Maria Marconi, Christopher Pal, Mohammad Emtiyaz Khan

NeurIPS 2022 On the Role of Overparameterization in Off-Policy Temporal Difference Learning with Linear Function Approximation Valentin Thomas

NeurIPS 2022 The Role of Baselines in Policy Gradient Optimization Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvari, Dale Schuurmans

NeurIPSW 2021 Beyond Target Networks: Improving Deep $q$-Learning with Functional Regularization Alexandre Piché, Joseph Marino, Gian Maria Marconi, Valentin Thomas, Christopher Pal, Mohammad Emtiyaz Khan

ICML 2021 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization Wesley Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux

AISTATS 2020 On the Interplay Between Noise and Curvature and Its Effect on Optimization and Generalization Valentin Thomas, Fabian Pedregosa, Bart Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux

ICLR 2019 Probabilistic Planning with Sequential Monte Carlo Methods Alexandre Piche, Valentin Thomas, Cyril Ibrahim, Yoshua Bengio, Chris Pal