关注
Pascal M. Esser
Pascal M. Esser
在 in.tum.de 的电子邮件经过验证
标题
引用次数
引用次数
年份
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
P Esser, L Chennuru Vankadara, D Ghoshdastidar
Advances in Neural Information Processing Systems (NeurIPS) 34, 2021
352021
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel
M Sabanayagam, P Esser, D Ghoshdastidar
Transactions on Machine Learning Research, 2023
9*2023
New Insights into Graph Convolutional Networks using Neural Tangent Kernels
M Sabanayagam, P Esser, D Ghoshdastidar
ECMLPKDD 2022, 18th International Workshop on Mining and Learning with Graphs, 2021
9*2021
Near-optimal comparison based clustering
M Perrot, P Esser, D Ghoshdastidar
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
72020
Non-Parametric Representation Learning with Kernels
P Esser, M Fleissner, D Ghoshdastidar
AAAI Conference on Artificial Intelligence (AAAI-24), 2023
22023
Towards Modeling and Resolving Singular Parameter Spaces using Stratifolds
PM Esser, F Nielsen
Advances in Neural Information Processing Systems 34, 13th Annual Workshop …, 2021
22021
Representation Learning Dynamics of Self-Supervised Models
P Esser, S Mukherjee, D Ghoshdastidar
Transactions on Machine Learning Research, 2024
12024
When can we Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis?
GG Anil, P Esser, D Ghoshdastidar
arXiv preprint arXiv:2403.08673, 2024
2024
Improved Representation Learning Through Tensorized Autoencoders
PM Esser, S Mukherjee, M Sabanayagam, D Ghoshdastidar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
2022
On the Influence of Enforcing Model Identifiability on Learning dynamics of Gaussian Mixture Models
PM Esser, F Nielsen
arXiv preprint arXiv:2206.08598, 2022
2022
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