AASAE: Augmentation-Augmented Stochastic Autoencoders

1 code implementation • 26 Jul 2021 • William Falcon, Ananya Harsh Jha, Teddy Koker, Kyunghyun Cho

We empirically evaluate the proposed AASAE on image classification, similar to how recent contrastive and non-contrastive learning algorithms have been evaluated.

Contrastive Learning Data Augmentation +2

A Framework For Contrastive Self-Supervised Learning And Designing A New Approach

1 code implementation • 31 Aug 2020 • William Falcon, Kyunghyun Cho

Contrastive self-supervised learning (CSL) is an approach to learn useful representations by solving a pretext task that selects and compares anchor, negative and positive (APN) features from an unlabeled dataset.

Data Augmentation Image Classification +1

Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons

1 code implementation • NeurIPS 2017 • Nikhil Parthasarathy, Eleanor Batty, William Falcon, Thomas Rutten, Mohit Rajpal, E.J. Chichilnisky, Liam Paninski

Decoding sensory stimuli from neural signals can be used to reveal how we sense our physical environment, and is valuable for the design of brain-machine interfaces.

Bayesian Inference

Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data

no code implementations • ICLR 2018 • William Falcon, Henning Schulzrinne

In cities with tall buildings, emergency responders need an accurate floor level location to find 911 callers quickly.