Search Results for author: Jason Ramapuram

Found 13 papers, 5 papers with code

Challenges of Adversarial Image Augmentations

no code implementations NeurIPS Workshop ICBINB 2021 Arno Blaas, Xavier Suau, Jason Ramapuram, Nicholas Apostoloff, Luca Zappella

Image augmentations applied during training are crucial for the generalization performance of image classifiers.

Evaluating the fairness of fine-tuning strategies in self-supervised learning

no code implementations1 Oct 2021 Jason Ramapuram, Dan Busbridge, Russ Webb

In this work we examine how fine-tuning impacts the fairness of contrastive Self-Supervised Learning (SSL) models.

Fairness Self-Supervised Learning

Stochastic Contrastive Learning

no code implementations1 Oct 2021 Jason Ramapuram, Dan Busbridge, Xavier Suau, Russ Webb

While state-of-the-art contrastive Self-Supervised Learning (SSL) models produce results competitive with their supervised counterparts, they lack the ability to infer latent variables.

Contrastive Learning Self-Supervised Learning

Do Self-Supervised and Supervised Methods Learn Similar Visual Representations?

no code implementations1 Oct 2021 Tom George Grigg, Dan Busbridge, Jason Ramapuram, Russ Webb

Despite the success of a number of recent techniques for visual self-supervised deep learning, there has been limited investigation into the representations that are ultimately learned.

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

1 code implementation ICCV 2021 Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Angel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind

To create our dataset, we leverage a large repository of synthetic scenes created by professional artists, and we generate 77, 400 images of 461 indoor scenes with detailed per-pixel labels and corresponding ground truth geometry.

Multi-Task Learning Natural Language Processing +2

Self-Supervised MultiModal Versatile Networks

1 code implementation NeurIPS 2020 Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelović, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman

In particular, we explore how best to combine the modalities, such that fine-grained representations of the visual and audio modalities can be maintained, whilst also integrating text into a common embedding.

Action Recognition In Videos Audio Classification +2

Improving Discrete Latent Representations With Differentiable Approximation Bridges

no code implementations9 May 2019 Jason Ramapuram, Russ Webb

Modern neural network training relies on piece-wise (sub-)differentiable functions in order to use backpropagation to update model parameters.

Density Estimation General Classification +3

Variational Saccading: Efficient Inference for Large Resolution Images

1 code implementation8 Dec 2018 Jason Ramapuram, Maurits Diephuis, Frantzeska Lavda, Russ Webb, Alexandros Kalousis

Image classification with deep neural networks is typically restricted to images of small dimensionality such as 224 x 244 in Resnet models [24].

General Classification Image Classification +2

Continual Classification Learning Using Generative Models

no code implementations24 Oct 2018 Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, Alexandros Kalousis

Continual learning is the ability to sequentially learn over time by accommodating knowledge while retaining previously learned experiences.

Classification Continual Learning +1

A New Benchmark and Progress Toward Improved Weakly Supervised Learning

1 code implementation30 Jun 2018 Jason Ramapuram, Russ Webb

Knowledge Matters: Importance of Prior Information for Optimization [7], by Gulcehre et.

Lifelong Generative Modeling

1 code implementation ICLR 2018 Jason Ramapuram, Magda Gregorova, Alexandros Kalousis

Lifelong learning is the problem of learning multiple consecutive tasks in a sequential manner, where knowledge gained from previous tasks is retained and used to aid future learning over the lifetime of the learner.

Transfer Learning

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