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08/25/2023
Fine-tuning can cripple your foundation model; preserving features may be the solution
Pre-trained foundation models, owing primarily to their enormous capacit...
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07/03/2023
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration
The current approach for testing the robustness of object detectors suff...
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05/27/2023
Graph Inductive Biases in Transformers without Message Passing
Transformers for graph data are increasingly widely studied and successf...
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09/24/2022
Raising the Bar on the Evaluation of Out-of-Distribution Detection
In image classification, a lot of development has happened in detecting ...
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07/22/2022
An Impartial Take to the CNN vs Transformer Robustness Contest
Following the surge of popularity of Transformers in Computer Vision, se...
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07/13/2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration
It is now well known that neural networks can be wrong with high confide...
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06/29/2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness
We show that the effectiveness of the well celebrated Mixup [Zhang et al...
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06/16/2022
Catastrophic overfitting is a bug but also a feature
Despite clear computational advantages in building robust neural network...
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02/02/2022
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training
Recently, Wong et al. showed that adversarial training with single-step ...
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07/09/2021
ANCER: Anisotropic Certification via Sample-wise Volume Maximization
Randomized smoothing has recently emerged as an effective tool that enab...
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04/01/2021
No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
There has been increasing interest in building deep hierarchy-aware clas...
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12/24/2020
On Batch Normalisation for Approximate Bayesian Inference
We study batch normalisation in the context of variational inference met...
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10/22/2020
Continual Learning in Low-rank Orthogonal Subspaces
In continual learning (CL), a learner is faced with a sequence of tasks,...
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10/10/2020
Diagnosing and Preventing Instabilities in Recurrent Video Processing
Recurrent models are becoming a popular choice for video enhancement tas...
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07/08/2020
How benign is benign overfitting?
We investigate two causes for adversarial vulnerability in deep neural n...
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06/16/2020
Progressive Skeletonization: Trimming more fat from a network at initialization
Recent studies have shown that skeletonization (pruning parameters) of n...
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04/20/2020
A Revised Generative Evaluation of Visual Dialogue
Evaluating Visual Dialogue, the task of answering a sequence of question...
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02/21/2020
Calibrating Deep Neural Networks using Focal Loss
Miscalibration – a mismatch between a model's confidence and its correct...
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02/19/2020
Using Hindsight to Anchor Past Knowledge in Continual Learning
In continual learning, the learner faces a stream of data whose distribu...
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10/18/2019
Mirror Descent View for Neural Network Quantization
Quantizing large Neural Networks (NN) while maintaining the performance ...
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09/24/2019
Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
Arnab Ghosh 6:32 PM We propose an interactive GAN-based sketch-to-image ...
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06/11/2019
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Exciting new work on the generalization bounds for neural networks (NN) ...
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02/27/2019
Continual Learning with Tiny Episodic Memories
Learning with less supervision is a major challenge in artificial intell...
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12/16/2018
Visual Dialogue without Vision or Dialogue
We characterise some of the quirks and shortcomings in the exploration o...
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12/11/2018
Proximal Mean-field for Neural Network Quantization
Compressing large neural networks by quantizing the parameters, while ma...
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09/24/2018
Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration
Deformable registration has been one of the pillars of biomedical image ...
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01/30/2018
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
We study the incremental learning problem for the classification task, a...
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07/19/2017
Deformable Registration through Learning of Context-Specific Metric Aggregation
We propose a novel weakly supervised discriminative algorithm for learni...
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07/18/2017
Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation
We propose an approach to discover class-specific pixels for the weakly-...
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04/10/2017
Multi-Agent Diverse Generative Adversarial Networks
This paper describes an intuitive generalization to the Generative Adver...
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05/30/2016
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
In this paper, we propose several improvements on the block-coordinate F...
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07/05/2015