Code for the hexagonal quantization algorithm for cartographic line simplification
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Updated
Jul 1, 2013 - Java
Code for the hexagonal quantization algorithm for cartographic line simplification
A Compositional Object-Based Approach to Learning Physical Dynamics
Simple tool to generalize raster file from change detection analysis. It combines generalization tools such as Majority Filter, Boundary Clean, Region group, Set Null and Nibble from ArcGIS Geoprocessing Tools
Published at Psychonomic Bulletin & Review:
Experiment consisting in learning error using an explicit generalization loss; implemented in Tensorflow
On the decision boundary of deep neural networks
Rcode for workshop on cross-validation in the Harvard Methods Dinner talk series
This is a machine learning project discovering different features of different model structures and visualize the optimization process
Computing various norms/measures on over-parametrized neural networks
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
ML/DL/RL paper notes
Equational Abstraction Via Least General Generalization
Supplementary code for the paper "Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks" - an accepted paper of LOD2019
Codes and experiments for "Multi-Class Learning: From Theory to Algorithm", published in NeurIPS 2018
Experiments related to optimization, convergence and network architectures.
This repository contains experimental setup for experiments conducted in 'Exploring numerical calculations with CalcNet' paper that was published in ICTAI 2019.
Semi-Supervised Learning by Disentangling and Self-Ensembling over Stochastic Latent Space. MICCAI 2019.
Fast and garbage-free Vector math library for any dimension.
Maze environment for DRL generalization studies
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