Popular GitHub Repositories for Bernoulli Trial

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Trial and Error: Exploration-Based Trajectory Optimization of LLM Agents (ACL 2024 Main Conference)

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.

AI Chatbot, Image Generator & Language Translator App | OpenAI ChatGPT | AI Assistant | Dart 3 & Flutter 3.13 ? with Free OpenAI Trial

GAN based ConvLSTM in precipitation prediction (Trial Version)

A clinical BERT-based NLP tool for parsing clinical trial abstracts following the PICO framework

A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.

Simple diffusion implementation for binary-valued data using a Bernoulli distribution instead of a Gaussian.

I aim in this project to analyze the sentiment of tweets provided from the Sentiment140 dataset by developing a machine learning sentiment analysis model involving the use of classifiers. The performance of these classifiers is then evaluated using accuracy and F1 scores.

A reimplementation of Andrej Karpathy's repository for an RL self-learning AI agent that learns to play Pong through trial and error, using PyTorch

Diego: Data in, IntElliGence Out. A fast framework that supports the rapid construction of automated learning tasks. Simply create an automated learning study (Study) and generate correlated trials (Trial). Then run the code and get a machine learning model. Implemented using Scikit-learn API glossary, using Bayesian optimization and genetic algorithms for automated machine learning. Inspired by [Fast.ai](https://github.com/fastai/fastai).

A toy example using an LLM to navigate a quadruped in an unknown environment through trial and error. Based on mujoco playground.

BERT trial for chinese corpus classfication

TI MSP432 programmed using embedded C to control an autonoumous 1/18-scale car to navigate a randomized track. Final project for RIT CMPE-460 IDE.

Hyperparameter Tuning with Microsoft NNI to automated machine learning (AutoML) experiments. The tool dispatches and runs trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different environments like local machine, remote servers and cloud.

Fitting and analysis of trial-based neural spike responses with Generalized Linear Model (GLM).

Vosk Speech Recognition Trial