695 Open source projects that are alternatives of or similar to Deformable Kernels

A structured light scanner

Redis operator build a Highly Available Redis cluster with Sentinel atop Kubernetes

Single C file, Realtime CPU/GPU Profiler with Remote Web Viewer

Vim operator mapping to enclose text objects with surrounds like paren, quote and so on.

Examples demonstrating available options to program multiple GPUs in a single node or a cluster

PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"

[ACM MM 2018] Attribute-Aware Attention Model for Fine-grained Representation Learning

oneAPI Math Kernel Library (oneMKL) Interfaces

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Extension package for spatial propagation network in pytorch.

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The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch

A Neural Network Toolkit.

Learned representation for Offline Handwritten Signature Verification. Models and code to extract features from signature images.

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💥💻💥 A data-parallel functional programming language

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CUDA Homomorphic Encryption Library

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A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).

Fast CUDA Kernels for ResNet Inference.

Helmut Hoffer von Ankershoffen experimenting with arm64 based NVIDIA Jetson (Nano and AGX Xavier) edge devices running Kubernetes (K8s) for machine learning (ML) including Jupyter Notebooks, TensorFlow Training and TensorFlow Serving using CUDA for smart IoT.

Semantic Entity Retrieval Toolkit

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Deep.Net machine learning framework for F#

Management UI for MinIO and MinIO operator

Extending JAX with custom C++ and CUDA code

ALgoloid with MAcros -- a language with Algol-family syntax where macros take center stage

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This is a Tensor Train based compression library to compress sparse embedding tables used in large-scale machine learning models such as recommendation and natural language processing. We showed this library can reduce the total model size by up to 100x in Facebook’s open sourced DLRM model while achieving same model quality. Our implementation is faster than the state-of-the-art implementations. Existing the state-of-the-art library also decompresses the whole embedding tables on the fly therefore they do not provide memory reduction during runtime of the training. Our library decompresses only the requested rows therefore can provide 10,000 times memory footprint reduction per embedding table. The library also includes a software cache to store a portion of the entries in the table in decompressed format for faster lookup and process.

The C++ Standard Library for your entire system.

Numeric Erlang - vector and matrix operations with CUDA. Heavily inspired by Pteracuda - https://github.com/kevsmith/pteracuda

JCuda - Java bindings for CUDA

Real-time dense visual SLAM system

A GitOps Operator for Kubernetes

Minimal Deep Learning library is written in Python/Cython/C++ and Numpy/CUDA/cuDNN.

Numerical linear algebra software package

A fast and highly scalable GPU dynamic memory allocator

EMNLP 2018: HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding

Deep learning with cats (^._.^)

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Execution primitives for C++

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QUDA is a library for performing calculations in lattice QCD on GPUs.

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A real time optical flow algorithm implemented on GPU