sansastra Goto Github PK

animal-human-cohabitation

Building an early warning system which detects wild animals near the road/rail with the help of wireless sensor networks and alerts passing vehicles of possible animal crossing.

anomaly-detection

Detecting automatic identification system (AIS) on-off switching anomalies, unusual turn detection, and deviation of trajectories of vessels.

clustering_ml

daas-delay

daas-variable

dc-reconfig

Topology and bandwidth reconfiguration simulation for datacenter and HPC networks using a Netbench simulator

dc_traffic_gen

Data center time varying traffic generator from real traces

defrag-analytical

defrag-hta

A JAVA-based simulator for evaluating defragmentation in elastic optical network with holding time awareness of traffic flows

defrag-hta-aux

A Java-based Simulator for Evaluating any Spectrum Allocation Policy and defragmentation in Elastic Optical Networks

evidential-deep-learning

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

javafilereadnsfpath

nsf-path

markov-modeling-eon

Model the resource allocation in eleastic optical networks using continuous time Markov chain.

markov-modeling-eon-df

Models the resource allocation with spectrum defragmentation in eleastic optical networks using continuous time Markov chain models.

netbench

Packet simulator for data center network topologies, routing, and congestion control

netbench-reconf

ngncs_hpc

hpc ngnc

philly-traces

pytorch-classification-uncertainty

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

sansastra.github.io

My website

trajectory-prediction

A python framework to predict trajectories of vessels with machine learning algorithms, such as lstm, seq2seq, etc.

uncertainty_edl_graph

Anomaly detection in maritime navigation with evidential deep learning based on graph-based clustering

wdm-pon

A Java-based simulator for wavelength division multiplexed or orthogonal frequency division multiplexed passive optical networks.