1 citations · 1 across the 4 of their papers we have counts for
5 papers
How the Hessian-Spectrum of Neural Networks Depends on Data
Jasraj Singh, Enea Monzio Compagnoni, Antonio Orvieto
The Hessian matrix is an important quantity of interest when it comes to studying the loss landscape and optimization dynamics in deep learning, as well as designing measures of ge…
Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference
Jasraj Singh, Shelvia Wongso, Jeremie Houssineau +1
Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models. However, its formulation depends on expectations and dive…
Effects of Dropout on Performance in Long-range Graph Learning Tasks
Jasraj Singh, Keyue Jiang, Brooks Paige +1
Message Passing Neural Networks (MPNNs) are a class of Graph Neural Networks (GNNs) that propagate information across the graph via local neighborhoods. The scheme gives rise to tw…
LingML: Linguistic-Informed Machine Learning for Enhanced Fake News Detection
Jasraj Singh, Fang Liu, Hong Xu +2
Nowadays, Information spreads at an unprecedented pace in social media and discerning truth from misinformation and fake news has become an acute societal challenge. Machine learni…
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh +2
Existing neural active learning algorithms have aimed to optimize the predictive performance of neural networks (NNs) by selecting data for labelling. However, other than a good pr…