25 citations · 119 across the 42 of their papers we have counts for
6 papers · 1 filter
Predicting the Reliability of an Image Classifier under Image Distortion
Dang Nguyen, Sunil Gupta, Kien Do +1
In image classification tasks, deep learning models are vulnerable to image distortions i.e. their accuracy significantly drops if the input images are distorted. An image-classifi…
Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks
Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran +3
Discovering new solid-state materials requires rapidly exploring the vast space of crystal structures and locating stable regions. Generating stable materials with desired properti…
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
Hung Le, Kien Do, Dung Nguyen +2
Effective decision-making in partially observable environments demands robust memory management. Despite their success in supervised learning, current deep-learning memory models s…
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime
Alistair Shilton, Sunil Gupta, Santu Rana +1
This paper presents two models of neural-networks and their training applicable to neural networks of arbitrary width, depth and topology, assuming only finite-energy neural activa…
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties
Arun Kumar A, Alistair Shilton, Sunil Gupta +3
Experimental (design) optimization is a key driver in designing and discovering new products and processes. Bayesian Optimization (BO) is an effective tool for optimizing expensive…
Embedding material graphs using the electron-ion potential: application to material fracture
Sherif Abdulkader Tawfik, Tri Minh Nguyen, Salvy P. Russo +3
At the heart of the flourishing field of machine learning potentials are graph neural networks, where deep learning is interwoven with physics-informed machine learning (PIML) arch…