On the Complexity of Exploration in Goal-Driven Navigation

16 Nov 20181 code implementation

Next, we propose to measure the complexity of each environment by constructing dependency graphs between the goals and analytically computing \emph{hitting times} of a random walk in the graph.

Neural Tangents: Fast and Easy Infinite Neural Networks in Python

5 Dec 20191 code implementation

Neural Tangents is a library designed to enable research into infinite-width neural networks.


On the Coherence of Fake News Articles

26 Jun 20191 code implementation

The generation and spread of fake news within new and online media sources is emerging as a phenomenon of high societal significance.

End-to-End Differentiable Physics for Learning and Control

NeurIPS 2018 1 code implementation

We present a differentiable physics engine that can be integrated as a module in deep neural networks for end-to-end learning.

You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery

24 May 20182 code implementations

We further explore resolution and object size requirements by systematically testing the pipeline at decreasing resolution, and conclude that objects only ~5 pixels in size can still be localized with high confidence.


Perturbative Neural Networks

CVPR 2018 3 code implementations

Convolutional neural networks are witnessing wide adoption in computer vision systems with numerous applications across a range of visual recognition tasks.

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

18 Dec 20163 code implementations

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline.


DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation

CVPR 2019 3 code implementations

In this work, we introduce DeepSDF, a learned continuous Signed Distance Function (SDF) representation of a class of shapes that enables high quality shape representation, interpolation and completion from partial and noisy 3D input data.


Deep Equilibrium Models

NeurIPS 2019 1 code implementation

We present a new approach to modeling sequential data: the deep equilibrium model (DEQ).


Scalable Methods for 8-bit Training of Neural Networks

NeurIPS 2018 4 code implementations

Armed with this knowledge, we quantize the model parameters, activations and layer gradients to 8-bit, leaving at a higher precision only the final step in the computation of the weight gradients.