8 papers
TRUST: Test-time Resource Utilization for Superior Trustworthiness
Haripriya Harikumar, Santu Rana
Standard uncertainty estimation techniques, such as dropout, often struggle to clearly distinguish reliable predictions from unreliable ones. We attribute this limitation to noisy…
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…
ECoDe: A Sample-Efficient Method for Co-Design of Robotic Agents
Kishan R. Nagiredla, Buddhika L. Semage, Arun Kumar A. +2
Co-designing autonomous robotic agents involves simultaneously optimizing the controller and physical design of the agent. Its inherent bi-level optimization formulation necessitat…
A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
Kiran Purohit, Soumi Das, Sourangshu Bhattacharya +1
Federated Learning systems are increasingly subjected to a multitude of model poisoning attacks from clients. Among these, edge-case attacks that target a small fraction of the inp…
Composite Concept Extraction through Backdooring
Banibrata Ghosh, Haripriya Harikumar, Khoa D Doan +2
Learning composite concepts, such as \textquotedbl red car\textquotedbl , from individual examples -- like a white car representing the concept of \textquotedbl car\textquotedbl{}…
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…