119 skills found · Page 1 of 4
VIDA-NYU / ReprozipReproZip is a tool that simplifies the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science.
bcs-iitk / BCS Workshop Apr 20Workshop on basic machine learning, computational modeling, psychophysics, basic data analysis and experiment design
shaoanlu / Mppi CbfColab notebooks showcasing experiments on MPPI (model predictive path integral control) and CBF (control barrier function). Utilizes jax to accelerate computation.
rkimura47 / Cmu Comp OrA series of tutorials for conducting computational experiments with optimization solvers
eytan / Www 15 TutorialMaterials for the WWW 2015 tutorial on online experiments for computational social science
CodeMonsterPHD / GaTector A Unified Framework For Gaze Object PredictionThis repository is the official implementation of GaTector, which studies the newly proposed task, gaze object prediction. In this work, we build a novel framework named GaTector to tackle the gaze object prediction problem in a unified way. Particularly, a specific-general-specific (SGS) feature extractor is firstly proposed to utilize a shared backbone to extract general features for both scene and head images. To better consider the specificity of inputs and tasks, SGS introduces two input-specific blocks before the shared backbone and three task-specific blocks after the shared backbone. Specifically, a novel defocus layer is designed to generate object-specific features for object detection task without losing information or requiring extra computations. Moreover, the energy aggregation loss is introduced to guide the gaze heatmap to concentrate on the stared box. In the end, we propose a novel mDAP metric that can reveal the difference between boxes even when they share no overlapping area. Extensive experiments on the GOO dataset verify the superiority of our method in all three tracks, i.e., object detection, gaze estimation, and gaze object prediction.
JimmyXtesla / BILNThe Bioinformatician’s Interactive Lab Notebook (BILN) is a smart, dynamic system for tracking experiments, datasets, and workflows. Designed for bioinformaticians, it ensures reproducibility, structured logging, and AI-readiness. Export logs, collaborate seamlessly, and let BILN become your interactive companion in computational biology.
zhangprofessor / Fast Non Local Means And Asymptotic Non Local MeansNon-Local means denoising (NLM) algorithm is a milestone algorithm in the field of image processing. The proposal of NLM has opened up the non-local method which has a deep influence. This paper performed a revisit for NLM from two aspects as follows: 1. To alleviate the high computational complexity problem of NLM, a fast algorithm was constructed, which was based on cross-correlation and fast Fourier transform; 2. NLM always blur structures and textures during the noise removal, especially in the case of strong noise. To solve this problem, an Asymptotic Non-Local Means image denoising algorithm is put forward, which uses the property of noise variance to control the filtering parameters. Numerical experiments illustrate that the fast algorithm is 27 times faster than classical implementation with standard parameter configuration, and the ANLM uniformly outperforms classical NLM, in terms of both PSNR and visual effects.
suchow / Awesome CrowdsA curated list of awesome resources on crowdsourcing, human computation, and online behavioral experiments.
pfi / MafWaf extension for writing computational experiments.
IBM / AdoAn extendible framework for executing benchmarks and computational experiments at scale
LeadingIndiaAI / Fake News Detection Fake news is misinformation or manipulated news that is spread across the social media with an intention to damage a person, agency and organisation. Due to the dissemination of fake news, there is a need for computational methods to detect them. Fake news detection aims to help users to expose varieties of fabricated news. To achieve this goal, first we have taken the datasets which contains both fake and real news and conducted various experiments to organize fake news detector. We used natural processing, machine learning and deep learning techniques to classify the datasets. We yielded a comprehensive audit of detecting fake news by including fake news categorization, existing algorithms from machine learning techniques. In this project, we explored different machine learning models like Naïve Bayes, K nearest neighbors, decision tree, random forest and deep learning networks like Shallow Convolutional Neural Networks (CNN), Deep Convolutional Neural Network (VDCNN), Long Short-Term Memory Network (LSTM), Gated Recurrent Unit Network (GRU), Combination of Convolutional Neural Network with Long Short-Term Memory (CNN-LSTM) and Convolutional Neural Network with Gated Recurrent Unit (CNN-LSTM).
JiangChSo / PFLMPrivacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradients. To achieve robustness to users dropping out, existing practical privacy-preserving federated learning schemes are based on (t, N)-threshold secret sharing. Such schemes rely on a strong assumption to guarantee security: the threshold t must be greater than half of the number of users. The assumption is so rigorous that in some scenarios the schemes may not be appropriate. Motivated by the issue, we first introduce membership proof for federated learning, which leverages cryptographic accumulators to generate membership proofs by accumulating users IDs. The proofs are issued in a public blockchain for users to verify. With membership proof, we propose a privacy-preserving federated learning scheme called PFLM. PFLM releases the assumption of threshold while maintaining the security guarantees. Additionally, we design a result verification algorithm based on a variant of ElGamal encryption to verify the correctness of aggregated results from the cloud server. The verification algorithm is integrated into PFLM as a part. Security analysis in a random oracle model shows that PFLM guarantees privacy against active adversaries. The implementation of PFLM and experiments demonstrate the performance of PFLM in terms of computation and communication.
ExperQuick / PyLabFlowPyLabFlow is a Python framework for managing, tracking, and reproducing complex computational experiments. Built for researchers, data scientists, and ML engineers, it provides component-level lineage, modular pipelines, and offline-first execution, making it easy to run, compare, and debug hundreds of experiments.
xw00616 / DEN ARMOEA# Introduction of DNN-AR-MOEA This repository contains code necessary to reproduce the experiments presented in Evolutionary Optimization of High-DimensionalMulti- and Many-Objective Expensive ProblemsAssisted by a Dropout Neural Network. Gaussian processes are widely used in surrogate-assisted evolutionary optimization of expensive problems. We propose a computationally efficient dropout neural network (EDN) to replace the Gaussian process and a new model management strategy to achieve a good balance between convergence and diversity for assisting evolutionary algorithms to solve high-dimensional multi- and many-objective expensive optimization problems. mainlydue to the ability to provide a confidence level of their outputs,making it possible to adopt principled surrogate managementmethods such as the acquisition function used in Bayesian opti-mization. Unfortunately, Gaussian processes become less practi-cal for high-dimensional multi- and many-objective optimizationas their computational complexity is cubic in the number oftraining samples. # References If you found DNN-AR-MOEA useful, we would be grateful if you cite the following reference: Evolutionary Optimization of High-DimensionalMulti- and Many-Objective Expensive ProblemsAssisted by a Dropout Neural Network (IEEE Transactions on Systems, Man and Cybernetics: Systems).
ericmedvet / JgeaJava General Evolutionary Algorithm (jgea) is a modular Java framework for experimenting with Evolutionary Computation.
jmwohl / SfpcExperiments and homework from the School for Poetic Computation
tzvc / Genetic PlaygroundA Javascript web application to explore and experiment with evolutionary computation principles.
marimo-team / ExpdRun computational experiments using marimo notebooks
microsoft / Angara.FlowA .NET framework for composing, evaluating, inspecting and persisting computational experiments which are represented as a dataflow.
