12 citations · 44 across the 15 of their papers we have counts for
5 papers · 1 filter
Design of Unmanned Air Vehicles Using Transformer Surrogate Models
Adam D. Cobb, Anirban Roy, Daniel Elenius +1
Computer-aided design (CAD) is a promising new area for the application of artificial intelligence (AI) and machine learning (ML). The current practice of design of cyber-physical…
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection
Ramneet Kaur, Susmit Jha, Anirban Roy +4
Machine learning methods such as deep neural networks (DNNs), despite their success across different domains, are known to often generate incorrect predictions with high confidence…
Detecting OODs as datapoints with High Uncertainty
Ramneet Kaur, Susmit Jha, Anirban Roy +3
Deep neural networks (DNNs) are known to produce incorrect predictions with very high confidence on out-of-distribution inputs (OODs). This limitation is one of the key challenges…
Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs
Ramneet Kaur, Susmit Jha, Anirban Roy +2
Deep neural networks (DNNs) are known to produce incorrect predictions with very high confidence on out-of-distribution (OOD) inputs. This limitation is one of the key challenges i…
Detecting Trojaned DNNs Using Counterfactual Attributions
Karan Sikka, Indranil Sur, Susmit Jha +2
We target the problem of detecting Trojans or backdoors in DNNs. Such models behave normally with typical inputs but produce specific incorrect predictions for inputs poisoned with…