Search Results for author:
Found 4 papers, 1 papers with code
Survey on Self-Supervised Multimodal Representation Learning and Foundation Models
Deep learning has been the subject of growing interest in recent years.
On effects of Knowledge Distillation on Transfer Learning
Through this work, we show that using guidance and knowledge from a larger teacher network during fine-tuning, we can improve the student network to achieve better validation performances like accuracy.
An Effective Baseline for Robustness to Distributional Shift
In this work we present a simple, but highly effective approach to deal with out-of-distribution detection that uses the principle of abstention: when encountering a sample from an unseen class, the desired behavior is to abstain from predicting.
Ranked #1 on
Out-of-Distribution Detection
on CIFAR-100
(using extra training data)
A Simple and Effective Baseline for Out-of-Distribution Detection using Abstention
In this work we present a simple, but highly effective approach to deal with out-of-distribution detection that uses the principle of abstention: when encountering a sample from an unseen class, the desired behavior is to abstain from predicting.
