Popular GitHub Repositories for Polynomial Arithmetic

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

[ACL 2023] Reasoning with Language Model Prompting: A Survey

Large collection of number systems providing custom arithmetic for mixed-precision algorithm development and optimization for AI, Machine Learning, Computer Vision, Signal Processing, CAE, EDA, control, optimization, estimation, and approximation.

Learning to create Machine Learning Algorithms

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:

Official Implementation of the CVPR'20 paper 'Π-nets: Deep Polynomial Neural Networks' and its T-PAMI-21 extension.

Machine Learning Concepts with Concepts

We introduce new zero-shot prompting magic words that improves the reasoning ability of language models: panel discussion!

Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units paper by trask et.al

An unofficial Python (Numpy and Pytorch) implementation of "Polyblur: Removing mild blur by polynomial reblurring" by Mauricio Delbracio and collaborators.

High order and sparse layers in pytorch. Lagrange Polynomial, Piecewise Lagrange Polynomial, Piecewise Discontinuous Lagrange Polynomial (Chebyshev nodes) and Fourier Series layers of arbitrary order. Piecewise implementations could be thought of as a 1d grid (for each neuron) where each grid element is Lagrange polynomial. Both full connected and convolutional layers included.

Intel’s HERACLES accelerator introduces a new set of fundamental instructions, the Polynomial Instructions Set Architecture (P-ISA) that operates directly on polynomials requiring a completely new programming environment. This open-source project aims at developing the building blocks for a compiler toolchain for HERACLES.

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Restore safety in fine-tuned language models through task arithmetic

Selected problems and their solutions from the book on "Machine Intelligence in Design Automation"

Sys2Bench is a benchmarking suite designed to evaluate reasoning and planning capabilities of large language models across algorithmic, logical, arithmetic, and common-sense reasoning tasks.

This repository demonstrates how to use AutoGen to integrate local and remote MCP (Model Context Protocol) servers. It showcases a local math tool (math_server.py) using Stdio and a remote Apify tool (RAG Web Browser Actor) via SSE for tasks like arithmetic and web browsing.

Probabilistic Response mOdel Fitting with Interactive Tools

In this repository I implemented all assignments in python for the purpose of learning python

This repo contains the files created for machine learning using python