| Quantifying the carbon emissions of machine learning A Lacoste, A Luccioni, V Schmidt, T Dandres arXiv preprint arXiv:1910.09700, 2019 | 842 | 2019 |
| CodeCarbon: estimate and track carbon emissions from machine learning computing V Schmidt, K Goyal, A Joshi, B Feld, L Conell, N Laskaris, D Blank, ... Cited on 20, 2021 | 81 | 2021 |
| A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems A Duval, SV Mathis, CK Joshi, V Schmidt, S Miret, FD Malliaros, T Cohen, ... arXiv preprint arXiv:2312.07511, 2023 | 59 | 2023 |
| Visualizing the consequences of climate change using cycle-consistent adversarial networks V Schmidt, A Luccioni, SK Mukkavilli, N Balasooriya, K Sankaran, ... arXiv preprint arXiv:1905.03709, 2019 | 54 | 2019 |
| Using artificial intelligence to visualize the impacts of climate change A Luccioni, V Schmidt, V Vardanyan, Y Bengio IEEE Computer Graphics and Applications 41 (1), 8-14, 2021 | 49 | 2021 |
| Faenet: Frame averaging equivariant gnn for materials modeling AA Duval, V Schmidt, A Hernández-Garcıa, S Miret, FD Malliaros, ... International Conference on Machine Learning, 9013-9033, 2023 | 45 | 2023 |
| Quantifying the carbon emissions of machine learning. arXiv A Lacoste, A Luccioni, V Schmidt, T Dandres arXiv preprint arXiv:1910.09700, 2019 | 31 | 2019 |
| CodeCarbon: estimate and track carbon emissions from machine learning computing (2021) V Schmidt, K Goyal, A Joshi, B Feld, L Conell, N Laskaris, D Blank, ... DOI: https://doi. org/10.5281/zenodo 4658424, 2021 | 25 | 2021 |
| Quantifying the carbon emissions of machine learning. arXiv 2019 A Lacoste, A Luccioni, V Schmidt, T Dandres arXiv preprint arXiv:1910.09700, 2019 | 25 | 2019 |
| Predicting infectiousness for proactive contact tracing Y Bengio, P Gupta, T Maharaj, N Rahaman, M Weiss, T Deleu, E Muller, ... arXiv preprint arXiv:2010.12536, 2020 | 23 | 2020 |
| Estimating carbon emissions of artificial intelligence [opinion] A Luccioni, A Lacoste, V Schmidt IEEE Technology and Society Magazine 39 (2), 48-51, 2020 | 23 | 2020 |
| Climategan: Raising climate change awareness by generating images of floods V Schmidt, AS Luccioni, M Teng, T Zhang, A Reynaud, S Raghupathi, ... arXiv preprint arXiv:2110.02871, 2021 | 17 | 2021 |
| Quantifying the carbon emissions of machine learning S Luccioni, V Schmidt, A Lacoste, T Dandres NeurIPS 2019 Workshop on Tackling Climate Change with Machine Learning, 2019 | 16 | 2019 |
| Handreiking schoolexamen informatica havo/vwo V Schmidt SLO, Enschede, 2006 | 16 | 2006 |
| mlco2/codecarbon: v2. 3.1 B Courty, V Schmidt, MC Goyal-Kamal, B Feld, J Lecourt, K SabAmine, ... Zenodo, 2023 | 15 | 2023 |
| COVI-AgentSim: an agent-based model for evaluating methods of digital contact tracing P Gupta, T Maharaj, M Weiss, N Rahaman, H Alsdurf, A Sharma, ... arXiv preprint arXiv:2010.16004, 2020 | 13 | 2020 |
| Crystal-gfn: sampling crystals with desirable properties and constraints M AI4Science, A Hernandez-Garcia, A Duval, A Volokhova, Y Bengio, ... arXiv preprint arXiv:2310.04925, 2023 | 9 | 2023 |
| PhAST: Physics-aware, scalable, and task-specific GNNs for accelerated catalyst design A Duval, V Schmidt, S Miret, Y Bengio, A Hernández-García, D Rolnick | 9 | 2023 |
| Proactive contact tracing P Gupta, T Maharaj, M Weiss, N Rahaman, H Alsdurf, N Minoyan, ... PLOS Digital Health 2 (3), e0000199, 2023 | 8 | 2023 |
| Using simulated data to generate images of climate change G Cosne, A Juraver, M Teng, V Schmidt, V Vardanyan, A Luccioni, ... arXiv preprint arXiv:2001.09531, 2020 | 8 | 2020 |
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