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05/26/2023
Rate-Distortion Theory in Coding for Machines and its Application
Recent years have seen a tremendous growth in both the capability and po...
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11/23/2022
FRE: A Fast Method For Anomaly Detection And Segmentation
This paper presents a fast and principled approach for solving the visua...
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08/24/2022
A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing
Split computing has emerged as a recent paradigm for implementation of D...
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02/16/2022
Anomalib: A Deep Learning Library for Anomaly Detection
This paper introduces anomalib, a novel library for unsupervised anomaly...
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09/13/2021
Improving Robustness and Efficiency in Active Learning with Contrastive Loss
This paper introduces supervised contrastive active learning (SCAL) by l...
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09/13/2021
Mitigating Sampling Bias and Improving Robustness in Active Learning
This paper presents simple and efficient methods to mitigate sampling bi...
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05/07/2021
Energy-Based Anomaly Detection and Localization
This brief sketches initial progress towards a unified energy-based solu...
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12/08/2020
Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features
This paper presents a principled approach for detecting out-of-distribut...
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12/18/2019
Tree pyramidal adaptive importance sampling
This paper introduces Tree-Pyramidal Adaptive Importance Sampling (TP-AI...
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12/03/2019
