96 citations · 298 across the 54 of their papers we have counts for
7 papers · 1 filter
AutoRSR: Automated Real-to-Sim-to-Real Data Generation for Scalable Robot Learning
Jiawei Zhang, Chang Liu, Litao Deng +2
Scaling embodied robot learning requires large and diverse manipulation datasets, but collecting real-world demonstrations remains expensive in human effort and robot time. Simulat…
Lifting Finite-Sample Gaussian Approximation of Wide Neural Networks to Functional Convergence
Luis Wiederhold, Nil Ayday, Debarghya Ghoshdastidar
Randomly initialised neural networks of width converge to Gaussian processes as , with two types of quantitative bounds characterising this convergence. Finite-sa…
An Analysis of Self-supervised Pre-training with Dependent Samples
Maximilian Fleissner, Debarghya Ghoshdastidar, Samory Kpotufe
Self-supervised learning relies on so-called data augmentations of unlabeled datapoints --- for example, masking random pixels in an image --- that should leave the…
Different Statistical Perspectives for Understanding Generalisation in Graph Neural Networks
Nil Ayday, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar
Graph Neural Networks (GNN) are currently the most popular approach for learning and prediction on graph-structured data and are deployed in various fields, from social network ana…
Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning
Ajinkya Mohgaonkar, Lukas Gosch, Mahalakshmi Sabanayagam +2
Label-flipping attacks, which corrupt training labels to induce misclassifications at inference, remain a major threat to supervised learning models. This drives the need for robus…
Gaussian Process Limit Reveals Structural Benefits of Graph Transformers
Nil Ayday, Lingchu Yang, Debarghya Ghoshdastidar
Graph transformers are the state-of-the-art for learning from graph-structured data and are empirically known to avoid several pitfalls of message-passing architectures. However, t…
Nonparametric Kernel Clustering with Bandit Feedback
Victor Thuot, Sebastian Vogt, Debarghya Ghoshdastidar +1
Clustering with bandit feedback refers to the problem of partitioning the arms of an -armed stochastic bandit according to their underlying distributions, based on noisy observa…