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ORCIDMichaël Defferrard
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2020 – today
- 2024
[c7]Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Michaël Defferrard, Elahe Rezaei, Ryan Carey, W. Rhett Davis, Rajeev Jain, Yusu Wang:
DE-HNN: An effective neural model for Circuit Netlist representation. AISTATS 2024: 4258-4266- [c6]Natasha Butt, Blazej Manczak, Auke J. Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen:
CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay. ICML 2024 - [i13]Natasha Butt, Blazej Manczak, Auke J. Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen:
CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay. CoRR abs/2402.04858 (2024) - [i12]Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Donghyeon Koh, Michaël Defferrard, Elahe Rezaei, Ryan Carey, W. Rhett Davis, Rajeev Jain, Yusu Wang:
DE-HNN: An effective neural model for Circuit Netlist representation. CoRR abs/2404.00477 (2024) - [i11]Sahil Manchanda, Dana Kianfar, Markus Peschl, Romain Lepert, Michaël Defferrard:
NeuroSteiner: A Graph Transformer for Wirelength Estimation. CoRR abs/2407.03792 (2024) - 2023
- [d2]Michaël Defferrard
, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson:
fma-small-tfds. Zenodo, 2023
- 2022
- [j3]Andreas Scheck, Stéphane Rosset, Michaël Defferrard, Andreas Loukas, Jaume Bonet, Pierre Vandergheynst, Bruno E. Correia:
RosettaSurf - A surface-centric computational design approach. PLoS Comput. Biol. 18(3) (2022) - 2021
- [i10]Jelena Banjac, Laurène Donati, Michaël Defferrard:
Learning to recover orientations from projections in single-particle cryo-EM. CoRR abs/2104.06237 (2021) - [i9]Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard:
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups. CoRR abs/2111.12139 (2021) - 2020
- [j2]Katharina Glomb, Joan Rué Queralt, David Pascucci, Michaël Defferrard, Sébastien Tourbier, Margherita Carboni, Maria Rubega, Serge Vulliémoz, Gijs Plomp, Patric Hagmann:
Connectome spectral analysis to track EEG task dynamics on a subsecond scale. NeuroImage 221: 117137 (2020) - [c5]Michaël Defferrard, Martino Milani, Frédérick Gusset, Nathanaël Perraudin:
DeepSphere: a graph-based spherical CNN. ICLR 2020 - [i8]Stefania Ebli, Michaël Defferrard, Gard Spreemann:
Simplicial Neural Networks. CoRR abs/2010.03633 (2020) - [i7]Michaël Defferrard, Martino Milani, Frédérick Gusset, Nathanaël Perraudin:
DeepSphere: a graph-based spherical CNN. CoRR abs/2012.15000 (2020)
2010 – 2019
- 2019
- [j1]Nathanaël Perraudin, Michaël Defferrard, Tomasz Kacprzak, Raphaël Sgier:
DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications. Astron. Comput. 27: 130-146 (2019) - [i6]Michaël Defferrard, Nathanaël Perraudin, Tomasz Kacprzak, Raphaël Sgier:
DeepSphere: towards an equivariant graph-based spherical CNN. CoRR abs/1904.05146 (2019) - 2018
- [c4]Youngjoo Seo, Michaël Defferrard, Pierre Vandergheynst, Xavier Bresson:
Structured Sequence Modeling with Graph Convolutional Recurrent Networks. ICONIP (1) 2018: 362-373 - [c3]Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé:
Learning to Recognize Musical Genre from Audio: Challenge Overview. WWW (Companion Volume) 2018: 1921-1922 - [i5]Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé:
Learning to Recognize Musical Genre from Audio. CoRR abs/1803.05337 (2018) - [i4]Nathanaël Perraudin, Michaël Defferrard, Tomasz Kacprzak, Raphaël Sgier:
DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications. CoRR abs/1810.12186 (2018) - 2017
- [c2]Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson:
FMA: A Dataset for Music Analysis. ISMIR 2017: 316-323 - [d1]Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson:
FMA: A Dataset For Music Analysis. UCI Machine Learning Repository, 2017 - 2016
- [c1]Michaël Defferrard, Xavier Bresson, Pierre Vandergheynst:
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. NIPS 2016: 3837-3845 - [i3]Michaël Defferrard, Xavier Bresson, Pierre Vandergheynst:
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. CoRR abs/1606.09375 (2016) - [i2]Kirell Benzi, Michaël Defferrard, Pierre Vandergheynst, Xavier Bresson:
FMA: A Dataset For Music Analysis. CoRR abs/1612.01840 (2016) - [i1]Youngjoo Seo, Michaël Defferrard, Pierre Vandergheynst, Xavier Bresson:
Structured Sequence Modeling with Graph Convolutional Recurrent Networks. CoRR abs/1612.07659 (2016)
Coauthor Index
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