Search Results for "paper"
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34 projects for "paper" with 2 filters applied:
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EssentialsX
The modern Essentials suite for Spigot and Paper
EssentialsX is a continuation of the Essentials plugin suite, updated to support modern Minecraft and Spigot versions. It provides countless new features, performance enhancements and fixes that are not available in the original Essentials or Spigot-Essentials. If you're coming from the original Essentials plugin, EssentialsX is a drop-in replacement for Essentials. -
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PaperSpine
Motivation-driven skill for learning from strong academic papers
...It is built for AI tools such as Codex, Claude Code, and OpenClaw, where the agent can follow structured writing workflows. The project asks the agent to study target formats and strong examples before drafting or revising. It emphasizes the central motivation of a paper, helping writers connect claims, structure, evidence, citations, and revisions into a coherent argument. The suite includes specialized skills for research, citation, rewriting, LaTeX, auditing, translation, humanization, and updates. It is best suited for users who need format-aware, evidence-aware academic writing support rather than generic text generation. -
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Kami
Good content deserves good paper
Kami is a minimalistic productivity tool designed to help users organize tasks, notes, and daily workflows in a clean and distraction-free interface. It focuses on simplicity, enabling users to capture ideas quickly and manage them efficiently without unnecessary complexity. The application is built with a modern design philosophy that emphasizes clarity and usability. It supports lightweight task management and note-taking features for personal productivity. Kami is suitable for users who... -
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YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
YOLOv9 is the official implementation of the paper “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.” It is a modern object detection repository focused on improving how deep networks preserve useful information during training. The project introduces Programmable Gradient Information and the GELAN architecture to improve gradient flow, parameter efficiency, and train-from-scratch performance. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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DeepMind Research
Implementations and code to accompany DeepMind publications
This repository collects reference implementations and illustrative code accompanying a wide range of DeepMind publications, making it easier for the research community to reproduce results, inspect algorithms, and build on prior work. The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics, MeshGraphNets for physics, RL Unplugged, Nowcasting for weather, and more. Each project folder typically includes its own README, scripts, and notebooks so you can run experiments or explore models in isolation, and many link to associated datasets or external environments like DeepMind Lab and StarCraft II. ... -
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sensible.vim
sensible.vim: Defaults everyone can agree on
...The philosophy is conservative: only enable settings that are broadly beneficial and unlikely to surprise seasoned users. It reduces the friction of onboarding to Vim by removing early paper cuts, letting you add personal preferences later from a sane baseline. The project acts as a living distillation of community wisdom about defaults that stand the test of time. By shipping just sensible toggles, it remains unobtrusive and easy to adopt in any dotfiles setup. -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
YOLOv7 is the official implementation of the paper “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.” It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. ... -
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YOLOR
implementation of paper - You Only Learn One Representation
YOLOR is the implementation of “You Only Learn One Representation,” a unified network approach for learning explicit and implicit knowledge together. The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts,... -
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Supervised Reptile
Code for the paper "On First-Order Meta-Learning Algorithms"
The supervised-reptile repository contains code associated with the paper “On First-Order Meta-Learning Algorithms”, which introduces Reptile, a meta-learning algorithm for learning model parameter initializations that adapt quickly to new tasks. The implementation here is aimed at supervised few-shot learning settings (e.g. Omniglot, Mini-ImageNet), not reinforcement learning, and includes scripts to run training and evaluation for few-shot classification. -
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s(ASP)
Implements the stable model semantics without grounding.
...This allows s(ASP) to execute programs that are not finitely groundable, including those which make use of lists and terms. Work on s(ASP) is supported by the National Science Foundation under Grant No. 1423419. Details of how s(ASP) works can be found in the following paper: Marple, Kyle, Elmer Salazar, and Gopal Gupta. "Computing Stable Models of Normal Logic Programs Without Grounding." arXiv preprint arXiv:1709.00501 (2017) (https://arxiv.org/abs/1709.00501). -
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Carbon library
A declarative library for building component-based user interfaces
...Since components made with Carbon can be works directly on SwiftUI, the cost of future migration can be greatly reduced. Uses DifferenceKit which is highly optimized based on Paul Heckel’s paper for diffing. Declarative design and diffing algorithm make your code more predictable, debugging easier and providing beautiful animations to users. -
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pybag
Crossplatform files synchronization and backup portable tool.
PYBAG implements a portable bag and is intended for fast synchronization and backup. It lets you use a portable digital storage device to carry your electronic documents similar to the way you can use a bag to carry paper documents. You can synchronize the bag with your original files easily. If a synchronization conflict occurs, it will be reported. You can specify rules for automatic conflict resolution. With PYBAG, you can backup files and synchronize any changes made to the original files with the bag. The synchronization process will only copy changed files. ... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution filters to extract n-gram features that are then pooled and fed into a classifier. The project includes scripts for training, evaluation, and data handling, making it easy to run experiments on datasets such as movie reviews or other labeled text collections. ... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates... -
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Deeplearning-papernotes
Summaries and notes on Deep Learning research papers
Deeplearning-papernotes is an implementation of Convolutional Neural Networks for sentence and text classification in TensorFlow, based on a well-known research paper that applies CNN architectures to natural language processing tasks with strong performance in sentiment analysis and similar classification problems. The repository provides the complete network definition, including an embedding layer to convert words into dense representations, convolution and max-pooling layers to extract informative features, and a final softmax classifier to distinguish between target classes. ... -
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Behaviour Control Framework
A C++ framework that uses inhibition trees for behaviour control.
The Behaviour Control Framework is a generic platform-independent C++ framework that implements a control architecture consisting of a hierarchical network of behaviour layers. These layers each contain behaviours that can inhibit one another and interact to achieve control. A full discussion of the structure and ideas behind this framework can be found in the Doxygen documentation that comes with the release. This documentation is well worth a read before you decide if the library is for... -
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State Controller Library
A C++ framework that implements generalised finite state machines.
The State Controller Library is a generic platform-independent C++ framework that allows finite state machines and multi-action planning generalisations thereof to be realised. The structure and implementation of this library focuses on the application of finite state machines to real-time control loops, but can be reasonably adapted for virtually any other application, even completely unrelated to control systems. An emphasis has been placed on having very low overhead so as not to hurt... -
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CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also... -
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Tufte-LaTeX
A Tufte-inspired LaTeX class for producing handouts, papers, and books
tufte-latex provides LaTeX classes for handouts and books inspired by Edward Tufte’s design principles, emphasizing clarity, readable measure, and rich marginalia. The classes feature wide side margins that host sidenotes, citations, and small figures, letting the main text flow without heavy footnote clutter. Built-in environments make it easy to place margin figures and tables, call out important points, and keep references close to the text they annotate. The typography favors generous... -
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The library for utilization of Minimal Quadtree format for storing very large sparse matrices. Please see the paper referenced below for the description of a problem. Corresponding papers: Tree-based Space Efficient Formats for Storing the Structure of Sparse Matrices (I. Šimeček, D. Langr, P. Tvrdík), In Scalable Computing: Practice and Experience, volume 15, 2014. Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures (I.
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oriDomi
Fold up DOM elements like paper
oriDomi is a JavaScript library that visually "folds" DOM elements like paper, creating origami-style transitions using CSS transforms and JavaScript. Use your mouse or touch to manipulate the images on the website, or press the fold button to see a random effect. Create an OriDomi instance by passing your target element to the constructor. When creating a new OriDomi composition, you can pass a map of options as the second argument. -
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer Vision and Pattern Recognition, 2012. This source code is provided without warranty and is available under the GPL license. ... -
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Approximate Subgraph Matching Algorithm
Approximate Subgraph Matching Algorithm for Dependency Graphs
...This Java implementation implements our ASM algorithm. See README file: https://sourceforge.net/projects/asmalgorithm/files/ If you use our ASM implementation to support academic research, please cite the following paper: Haibin Liu, Lawrence Hunter, Vlado Keselj, and Karin Verspoor. Approximate Subgraph Matching-based Literature Mining for Biomedical Events and Relations. PLOS ONE, 8:4 e60954, 2013. -
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Exact Subgraph Matching Algorithm
Exact Subgraph Matching Algorithm for Dependency Graphs
...This Java implementation implements our ESM algorithm. See README file: https://sourceforge.net/projects/esmalgorithm/files/ If you use our ESM implementation to support academic research, please cite the following paper: Haibin Liu, Vlado Keselj, and Christian Blouin. Exploring a Subgraph Matching Approach for Extracting Biological Events from Literature. Computational Intelligence, 2013.
