most citedSource-free Domain Adaptation Requires Penalized Diversity

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Auxiliary Losses for Learning Generalizable Concept-based Models

Ivaxi Sheth, Samira Ebrahimi Kahou

The increasing use of neural networks in various applications has lead to increasing apprehensions, underscoring the necessity to understand their operations beyond mere final pred…

cs.LG2023

Transparent Anomaly Detection via Concept-based Explanations

Laya Rafiee Sevyeri, Ivaxi Sheth, Farhood Farahnak +2

Advancements in deep learning techniques have given a boost to the performance of anomaly detection. However, real-world and safety-critical applications demand a level of transpar…

cs.CV2023

WiCV@CVPR2023: The Eleventh Women In Computer Vision Workshop at the Annual CVPR Conference

Doris Antensteiner, Marah Halawa, Asra Aslam +6

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2023, organized alongside the hybrid CVPR 2023 in Vancouver, Canada. WiCV aims to amplify the voic…

cs.LG20231 cited

Source-free Domain Adaptation Requires Penalized Diversity

Laya Rafiee Sevyeri, Ivaxi Sheth, Farhood Farahnak +4

While neural networks are capable of achieving human-like performance in many tasks such as image classification, the impressive performance of each model is limited to its own dat…

cs.CV2022

WiCV 2022: The Tenth Women In Computer Vision Workshop

Doris Antensteiner, Silvia Bucci, Arushi Goel +6

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2022, organized alongside the hybrid CVPR 2022 in New Orleans, Louisiana. It provides a voice to a…