Pascal Mattia Esser

20 papers A* 4A 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Probabilistic Model for Self-Supervised Learning. CoRR Maximilian Fleissner, Pascal Mattia Esser, Debarghya Ghoshdastidar
2025	J	`jnl`	Theoretical Foundations of Representation Learning using Unlabeled Data: Statistics and Optimization. CoRR Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar
2025	A*	`conf`	When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? AAAI Gautham Govind Anil, Pascal Mattia Esser, Debarghya Ghoshdastidar
2024	J	`jnl`	Cluster Specific Representation Learning. CoRR Mahalakshmi Sabanayagam, Omar Al-Dabooni, Pascal Mattia Esser
2024	A*	`conf`	Non-parametric Representation Learning with Kernels. AAAI Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar
2024	J	`jnl`	Representation Learning Dynamics of Self-Supervised Models. Trans. Mach. Learn. Res. Pascal Mattia Esser, Satyaki Mukherjee, Debarghya Ghoshdastidar
2024	J	`jnl`	When can we Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? CoRR Gautham Govind Anil, Pascal Mattia Esser, Debarghya Ghoshdastidar
2023	J	`jnl`	Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel. Trans. Mach. Learn. Res. Mahalakshmi Sabanayagam, Pascal Mattia Esser, Debarghya Ghoshdastidar
2023	A	`conf`	Improved Representation Learning Through Tensorized Autoencoders. AISTATS Pascal Mattia Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar
2023	J	`jnl`	Non-Parametric Representation Learning with Kernels. CoRR Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar
2023	J	`jnl`	Representation Learning Dynamics of Self-Supervised Models. CoRR Pascal Mattia Esser, Satyaki Mukherjee, Debarghya Ghoshdastidar
2022	J	`jnl`	Improved Representation Learning Through Tensorized Autoencoders. CoRR Pascal Mattia Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar
2022	J	`jnl`	On the Influence of Enforcing Model Identifiability on Learning dynamics of Gaussian Mixture Models. CoRR Pascal Mattia Esser, Frank Nielsen
2022	J	`jnl`	Representation Power of Graph Convolutions : Neural Tangent Kernel Analysis. CoRR Mahalakshmi Sabanayagam, Pascal Mattia Esser, Debarghya Ghoshdastidar
2021	A*	`conf`	Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks. NeurIPS Pascal Mattia Esser, Leena C. Vankadara, Debarghya Ghoshdastidar
2021	J	`jnl`	Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks. CoRR Pascal Mattia Esser, Leena C. Vankadara, Debarghya Ghoshdastidar
2021	J	`jnl`	New Insights into Graph Convolutional Networks using Neural Tangent Kernels. CoRR Mahalakshmi Sabanayagam, Pascal Mattia Esser, Debarghya Ghoshdastidar
2021	J	`jnl`	Towards Modeling and Resolving Singular Parameter Spaces using Stratifolds. CoRR Pascal Mattia Esser, Frank Nielsen
2020	A*	`conf`	Near-Optimal Comparison Based Clustering. NeurIPS Michaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar
2020	J	`jnl`	Near-Optimal Comparison Based Clustering. CoRR Michaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar