Vikas Verma | DeepAI

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∙ 12/27/2022

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective

Mixup is a popular data augmentation technique for training deep neural ...

0 Vikas Verma, et al. ∙

∙ 10/18/2022

CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback

We propose a novel regularizer for supervised learning called Conditioni...

11 Alexia Jolicoeur-Martineau, et al. ∙

∙ 11/09/2020

Towards Domain-Agnostic Contrastive Learning

Despite recent success, most contrastive self-supervised learning method...

0 Vikas Verma, et al. ∙

∙ 06/14/2020

PatchUp: A Regularization Technique for Convolutional Neural Networks

Large capacity deep learning models are often prone to a high generaliza...

42 Mojtaba Faramarzi, et al. ∙

∙ 06/03/2020

Interpolation-based semi-supervised learning for object detection

Despite the data labeling cost for the object detection tasks being subs...

3 Jisoo Jeong, et al. ∙

∙ 12/25/2019

SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks

Deep networks have achieved excellent results in perceptual tasks, yet t...

40 Alex Lamb, et al. ∙

∙ 09/25/2019

GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning

We present GraphMix, a regularization technique for Graph Neural Network...

4 Vikas Verma, et al. ∙

∙ 07/16/2019

Towards Understanding Generalization in Gradient-Based Meta-Learning

In this work we study generalization of neural networks in gradient-base...

9 Simon Guiroy, et al. ∙

∙ 06/16/2019

Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy

Adversarial robustness has become a central goal in deep learning, both ...

11 Alex Lamb, et al. ∙

∙ 03/09/2019

Interpolation Consistency Training for Semi-Supervised Learning

We introduce Interpolation Consistency Training (ICT), a simple and comp...

10 Vikas Verma, et al. ∙

∙ 03/07/2019

Adversarial Mixup Resynthesizers

In this paper, we explore new approaches to combining information encode...

12 Christopher Beckham, et al. ∙

∙ 06/18/2018

Modularity Matters: Learning Invariant Relational Reasoning Tasks

We focus on two supervised visual reasoning tasks whose labels encode a ...

0 Jason Jo, et al. ∙

∙ 06/13/2018

Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer

Deep networks often perform well on the data manifold on which they are ...

0 Vikas Verma, et al. ∙

∙ 10/13/2017

Residual Connections Encourage Iterative Inference

Residual networks (Resnets) have become a prominent architecture in deep...

0 Stanisław Jastrzębski, et al. ∙

∙ 02/28/2017

Deep Semi-Random Features for Nonlinear Function Approximation

We propose semi-random features for nonlinear function approximation. Th...

0 Kenji Kawaguchi, et al. ∙

∙ 09/02/2014

Image Retrieval And Classification Using Local Feature Vectors

Content Based Image Retrieval(CBIR) is one of the important subfield in ...

0 Vikas Verma, et al. ∙

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