114 skills found · Page 1 of 4
chaitin / BlazehttpBlazeHTTP 是一款简单易用的 WAF 防护效果测试工具。BlazeHTTP stands as a user-friendly WAF protection efficacy evaluation tool.
microsoft / Windows Dev PerformanceA repo for developers on Windows to file issues that impede their productivity, efficiency, and efficacy
sdv-dev / SDMetricsMetrics to evaluate quality and efficacy of synthetic datasets.
openappsec / Waf Comparison ProjectTesting datasets and tools to compare WAF efficacy
holistic-ai / HolisticaiThis is an open-source tool to assess and improve the trustworthiness of AI systems.
helenl9098 / Dynamic Diffuse Global Illumination MinecraftDDGI Minecraft is based on the 2019 SIGGRAPH paper, Dynamic Diffuse Global Illumination with Ray-Traced Irradiance Fields (2019), where we aimed to approximate indirect lighting and global illumination in Minecraft-inspired scenes using Vulkan to test the algorithm's efficacy in real-time.
sander-wood / Text To MusicExploring the Efficacy of Pre-trained Checkpoints in Text-to-Music Generation Task [AAAI 2023 Workshop]
kekegg / DLEPSA Deep Learning based Efficacy Prediction System for drug discovery
aliasgharheidaricom / Slime Mould Algorithm A New Method For Stochastic Optimization In this paper, a new stochastic optimizer, which is called slime mould algorithm (SMA), is proposed based upon the oscillation mode of slime mould in nature. The proposed SMA has several new features with a unique mathematical model that uses adaptive weights to simulate the process of producing positive and negative feedback of the propagation wave of slime mould based on bio-oscillator to form the optimal path for connecting food with excellent exploratory ability and exploitation propensity. The proposed SMA is compared with up-to-date metaheuristics in an extensive set of benchmarks to verify the efficiency. Moreover, four classical engineering structure problems are utilized to estimate the efficacy of the algorithm in optimizing engineering problems. The results demonstrate that the algorithm proposed benefits from competitive, often outstanding performance on different search landscapes. The source codes and info of SMA are publicly available at: http://www.alimirjalili.com/SMA.html
microsoft / DELTDELT: Data Efficacy for Language Model Training
lijiazheng99 / Counterfactuals For Sentiment AnalysisACL-21 Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis
jagar2 / Revealing Ferroelectric Switching Character Using Deep Recurrent Neural NetworksThe ability to manipulate domains and domain walls underpins function in a range of next-generation applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properties, such approaches lack an internal feedback loop required for automation. Here, using a deep sequence-to-sequence autoencoder we automate the extraction of features of nanoscale ferroelectric switching from multichannel hyperspectral band-excitation piezoresponse force microscopy of tensile-strained PbZr0.2Ti0.8O3 with a hierarchical domain structure. Using this approach, we identify characteristic behavior in the piezoresponse and cantilever resonance hysteresis loops, which allows for the classification and quantification of nanoscale-switching mechanisms. Specifically, we are able to identify elastic hardening events which are associated with the nucleation and growth of charged domain walls. This work demonstrates the efficacy of unsupervised neural networks in learning features of the physical response of a material from nanoscale multichannel hyperspectral imagery and provides new capabilities in leveraging multimodal in operando spectroscopies and automated control for the manipulation of nanoscale structures in materials.
paras2612 / CauseBoxCausal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensignificant advances through the application of machine learningtechniques, especially deep neural networks. Unfortunately, to-datemany of the proposed methods are evaluated on different (data,software/hardware, hyperparameter) setups and consequently it isnearly impossible to compare the efficacy of the available methodsor reproduce results presented in original research manuscripts.In this paper, we propose a causal inference toolbox (CauseBox)that addresses the aforementioned problems. At the time of thewriting, the toolbox includes seven state of the art causal inferencemethods and two benchmark datasets. By providing convenientcommand-line and GUI-based interfaces, theCauseBoxtoolboxhelps researchers fairly compare the state of the art methods intheir chosen application context against benchmark datasets.
HANMA97 / BiRiskRRTValidate the Efficacy of BiRiskRRT
Rash023 / MediquityA pinnacle of healthcare innovation, where cutting-edge AI meets compassionate care. Our platform is a symphony of precision and efficacy, harnessing the boundless potential of artificial intelligence to revolutionize wellness.
Kasyfil97 / Fraud Transaction Detection By Balancing DistributionImagine standing at the check-out counter at the grocery store with a long line behind you and the cashier not-so-quietly announces that your card has been declined. In this moment, you probably aren’t thinking about the data science that determined your fate. Embarrassed, and certain you have the funds to cover everything needed for an epic nacho party for 50 of your closest friends, you try your card again. Same result. As you step aside and allow the cashier to tend to the next customer, you receive a text message from your bank. “Press 1 if you really tried to spend $500 on cheddar cheese.” While perhaps cumbersome (and often embarrassing) in the moment, this fraud prevention system is actually saving consumers millions of dollars per year. Researchers from the IEEE Computational Intelligence Society (IEEE-CIS) want to improve this figure, while also improving the customer experience. With higher accuracy fraud detection, you can get on with your chips without the hassle. IEEE-CIS works across a variety of AI and machine learning areas, including deep neural networks, fuzzy systems, evolutionary computation, and swarm intelligence. Today they’re partnering with the world’s leading payment service company, Vesta Corporation, seeking the best solutions for fraud prevention industry, and now you are invited to join the challenge. In this competition, you’ll benchmark machine learning models on a challenging large-scale dataset. The data comes from Vesta's real-world e-commerce transactions and contains a wide range of features from device type to product features. You also have the opportunity to create new features to improve your results. If successful, you’ll improve the efficacy of fraudulent transaction alerts for millions of people around the world, helping hundreds of thousands of businesses reduce their fraud loss and increase their revenue. And of course, you will save party people just like you the hassle of false positives. Acknowledgements: Vesta Corporation provided the dataset for this competition. Vesta Corporation is the forerunner in guaranteed e-commerce payment solutions. Founded in 1995, Vesta pioneered the process of fully guaranteed card-not-present (CNP) payment transactions for the telecommunications industry. Since then, Vesta has firmly expanded data science and machine learning capabilities across the globe and solidified its position as the leader in guaranteed ecommerce payments. Today, Vesta guarantees more than $18B in transactions annually.
goldingn / Neuts2efficacymodelling SARS-CoV-2 vaccine efficacy from antibody titres, and impact of waning and variants on transmission
theheraldproject / Theheraldproject.github.ioHerald - Proximity Detection Protocol and research documentation, including the Fair Efficacy Formula
WOWNICE / Ssl SmallCode implementation for paper "On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals".
liambll / Drug Efficacy PredictionPredicting anti-HIV activity of chemical molecules - Python, RDKit, Scikit-learn, Keras, Tensorflow
