The Dutch Situation: An Ever Continuing Story. - Bert Zwaneveld; Victor Schmidt (Reflections on the History of Computers in Education, 2014)

Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks. - Victor Schmidt; Alexandra Luccioni; S. Karthik Mukkavilli; Narmada Balasooriya; Kris Sankaran; Jennifer T. Chayes; Yoshua Bengio (CoRR, 2019)

Quantifying the Carbon Emissions of Machine Learning. - Alexandre Lacoste; Alexandra Luccioni; Victor Schmidt; Thomas Dandres (CoRR, 2019)

Using Simulated Data to Generate Images of Climate Change. - Gautier Cosne; Adrien Juraver; Mélisande Teng; Victor Schmidt; Vahe Vardanyan; Alexandra Luccioni; Yoshua Bengio (CoRR, 2020)

Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation. - Victor Schmidt; Makesh Narsimhan Sreedhar; Mostafa ElAraby; Irina Rish (CoRR, 2020)

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. - Matthew Amodio; Rim Assouel; Victor Schmidt; Tristan Sylvain; Smita Krishnaswamy; Yoshua Bengio (CoRR, 2020)

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. - Prateek Gupta; Tegan Maharaj; Martin Weiss; Nasim Rahaman; Hannah Alsdurf; Abhinav Sharma; Nanor Minoyan; Soren Harnois-Leblanc; Victor Schmidt; Pierre-Luc St-Charles; Tristan Deleu; Andrew Williams; et al. (CoRR, 2020)

Estimating Carbon Emissions of Artificial Intelligence [Opinion]. - Alexandra Luccioni; Alexandre Lacoste; Victor Schmidt (IEEE Technol. Soc. Mag., 2020)

Predicting Infectiousness for Proactive Contact Tracing. - Yoshua Bengio; Prateek Gupta; Tegan Maharaj; Nasim Rahaman; Martin Weiss; Tristan Deleu; Eilif Benjamin Müller; Meng Qu; Victor Schmidt; Pierre-Luc St-Charles; Hannah Alsdurf; Olexa Bilaniuk; et al. (ICLR, 2021)

Using Artificial Intelligence to Visualize the Impacts of Climate Change. - Alexandra Luccioni; Victor Schmidt; Vahe Vardanyan; Yoshua Bengio; Theresa-Marie Rhyne (IEEE Computer Graphics and Applications, 2021)

ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. - Victor Schmidt; Alexandra Luccioni; Mélisande Teng; Tianyu Zhang; Alexia Reynaud; Sunand Raghupathi; Gautier Cosne; Adrien Juraver; Vahe Vardanyan; Alex Hernández-García; Yoshua Bengio (ICLR, 2022)

FAENet: Frame Averaging Equivariant GNN for Materials Modeling. - Alexandre Duval; Victor Schmidt; Alex Hernández-García; Santiago Miret; Fragkiskos D. Malliaros; Yoshua Bengio; David Rolnick (ICML, 2023)

torchgfn: A PyTorch GFlowNet library. - Salem Lahlou; Joseph D. Viviano; Victor Schmidt (CoRR, 2023)

Crystal-GFN: sampling crystals with desirable properties and constraints. - Alex Hernández-García; Alexandre Duval; Alexandra Volokhova; Yoshua Bengio; Divya Sharma; Pierre Luc Carrier; Michal Koziarski; Victor Schmidt (CoRR, 2023)

On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions. - Alvaro Carbonero; Alexandre Duval; Victor Schmidt; Santiago Miret; Alex Hernández-García; Yoshua Bengio; David Rolnick (CoRR, 2023)

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. - Alexandre Duval; Simon V. Mathis; Chaitanya K. Joshi; Victor Schmidt; Santiago Miret; Fragkiskos D. Malliaros; Taco Cohen; Pietro Lio; Yoshua Bengio; Michael M. Bronstein (CoRR, 2023)

Improving Molecular Modeling with Geometric GNNs: an Empirical Study. - Ali Ramlaoui; Théo Saulus; Basile Terver; Victor Schmidt; David Rolnick; Fragkiskos D. Malliaros; Alexandre Duval (CoRR, 2024)

PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design. - Alexandre Duval; Victor Schmidt; Santiago Miret; Yoshua Bengio; Alex Hernández-García; David Rolnick (J. Mach. Learn. Res., 2024)