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2020 – today
- 2024
[j2]Pascal Mattia Esser, Satyaki Mukherjee, Debarghya Ghoshdastidar:
Representation Learning Dynamics of Self-Supervised Models. Trans. Mach. Learn. Res. 2024 (2024)- [c4]Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar:
Non-parametric Representation Learning with Kernels. AAAI 2024: 11910-11918 - [i10]Gautham Govind Anil, Pascal Mattia Esser, Debarghya Ghoshdastidar:
When can we Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? CoRR abs/2403.08673 (2024) - 2023
- [j1]Mahalakshmi Sabanayagam, Pascal Mattia Esser, Debarghya Ghoshdastidar:
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel. Trans. Mach. Learn. Res. 2023 (2023) - [c3]Pascal Mattia Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar:
Improved Representation Learning Through Tensorized Autoencoders. AISTATS 2023: 8294-8307 - [i9]Pascal Mattia Esser, Satyaki Mukherjee, Debarghya Ghoshdastidar:
Representation Learning Dynamics of Self-Supervised Models. CoRR abs/2309.02011 (2023) - [i8]Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar:
Non-Parametric Representation Learning with Kernels. CoRR abs/2309.02028 (2023) - 2022
- [i7]Pascal Mattia Esser, Frank Nielsen
:
On the Influence of Enforcing Model Identifiability on Learning dynamics of Gaussian Mixture Models. CoRR abs/2206.08598 (2022) - [i6]Mahalakshmi Sabanayagam, Pascal Mattia Esser, Debarghya Ghoshdastidar:
Representation Power of Graph Convolutions : Neural Tangent Kernel Analysis. CoRR abs/2210.09809 (2022) - [i5]Pascal Mattia Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar:
Improved Representation Learning Through Tensorized Autoencoders. CoRR abs/2212.01046 (2022) - 2021
- [c2]Pascal Mattia Esser, Leena C. Vankadara, Debarghya Ghoshdastidar:
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks. NeurIPS 2021: 27043-27056 - [i4]Mahalakshmi Sabanayagam, Pascal Mattia Esser, Debarghya Ghoshdastidar:
New Insights into Graph Convolutional Networks using Neural Tangent Kernels. CoRR abs/2110.04060 (2021) - [i3]Pascal Mattia Esser, Frank Nielsen:
Towards Modeling and Resolving Singular Parameter Spaces using Stratifolds. CoRR abs/2112.03734 (2021) - [i2]Pascal Mattia Esser, Leena C. Vankadara, Debarghya Ghoshdastidar:
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks. CoRR abs/2112.03968 (2021) - 2020
- [c1]Michaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar:
Near-Optimal Comparison Based Clustering. NeurIPS 2020 - [i1]Michaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar:
Near-Optimal Comparison Based Clustering. CoRR abs/2010.03918 (2020)
Coauthor Index
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