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2020 – today
- 2023
[c4]Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh:
Equivariance with Learned Canonicalization Functions. ICML 2023: 15546-15566- [c3]Arnab Kumar Mondal, Siba Smarak Panigrahi, Oumar Kaba, Sai Mudumba, Siamak Ravanbakhsh:
Equivariant Adaptation of Large Pretrained Models. NeurIPS 2023 - [i7]Daniel T. Levy, Sékou-Oumar Kaba, Carmelo Gonzales, Santiago Miret, Siamak Ravanbakhsh:
Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks. CoRR abs/2309.03139 (2023) - [i6]Arnab Kumar Mondal, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh:
Equivariant Adaptation of Large Pretrained Models. CoRR abs/2310.01647 (2023) - [i5]Sékou-Oumar Kaba, Siamak Ravanbakhsh:
Symmetry Breaking and Equivariant Neural Networks. CoRR abs/2312.09016 (2023) - 2022
- [c2]Sékou-Oumar Kaba, Siamak Ravanbakhsh:
Equivariant Networks for Crystal Structures. NeurIPS 2022 - [i4]Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh:
Equivariance with Learned Canonicalization Functions. CoRR abs/2211.06489 (2022) - [i3]Sékou-Oumar Kaba, Siamak Ravanbakhsh:
Equivariant Networks for Crystal Structures. CoRR abs/2211.15420 (2022) - 2021
- [c1]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS 2021: 1256-1272 - [i2]Sékou-Oumar Kaba, Benjamin Groleau-Paré, Marc-Antoine Gauthier, André-Marie Tremblay, Simon Verret, Chloé Gauvin-Ndiaye:
Prediction of Large Magnetic Moment Materials With Graph Neural Networks and Random Forests. CoRR abs/2111.14712 (2021) - 2020
- [i1]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR abs/2011.09468 (2020)
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