Python Jerk-constrained Resources

Cooper About Cooper is a toolkit for Lagrangian-based constrained optimization in Pytorch. This library aims to encourage and facilitate the study of

Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli

PolytopeSampler PolytopeSampler is a Matlab implementation of constrained Riemannian Hamiltonian Monte Carlo for sampling from high dimensional disrib

Constrained Language Models Yield Few-Shot Semantic Parsers This repository contains tools and instructions for reproducing the experiments in the pap

Lipschitz-constrained Unsupervised Skill Discovery This repository is the official implementation of Seohong Park, Jongwook Choi*, Jaekyeom Kim*, Hong

Ruckig Instantaneous Motion Generation for Robots and Machines. Ruckig generates trajectories on-the-fly, allowing robots and machines to react instan

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BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func

Constrained Logistic Regression Sample implementation of constructing a logistic regression with given ranges on each of the feature's coefficients (v

SFace Code of TIP2021 Paper 《SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition》. We provide both MxNet, PyTorch and Jittor versi

CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ

Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.

Pre-train or Annotate? Domain Adaptation with a Constrained Budget This repo contains code and data associated with EMNLP 2021 paper "Pre-train or Ann

sNewton4PDEOpt The Python module implements a semismooth Newton method for solving finite-element discretizations of the strongly convex, linear ellip

Multi-objective constrained optimization for energy applications via tree ensembles

OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio

LOCKER This is the pytorch implementation of this paper: Locally Constrained Self-Attentive Sequential Recommendation. Zhankui He, Handong Zhao, Zhe L

GDAP Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works Environment Python (verified: v3.8) CUDA

(Subspace Constrained) Mean Shift Algorithms in Euclidean and/or Directional Product Spaces This repository contains Python3 code for the mean shift a

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search This repository is the official implementation of CAPITAL: Optimal Subgrou

model_based_energy_constrained_compression Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and

This is the official implementation of the following paper: Torsten Scholak, Nathan Schucher, Dzmitry Bahdanau. PICARD - Parsing Incrementally for Con

[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La

MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. The constraints are defined as upper bounds on sub-objective loss function. MooGBT uses a Augmented Lagrangian(AL) based constrained optimization framework with Gradient Boosted Trees, to optimize for multiple objectives.

CoSA is a scheduler for spatial DNN accelerators that generate high-performance schedules in one shot using mixed integer programming

NLopt is a library for nonlinear local and global optimization, for functions with and without gradient information. It is designed as a simple, unifi

The MicroPython project This is the MicroPython project, which aims to put an implementation of Python 3.x on microcontrollers and small embedded syst