Compile-time Dependency Injection for Go
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Aug 22, 2025 - Go
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Educational/research monocular visual odometry implementation with ORB features, initialization, tracking, local mapping, and bundle adjustment in C++.
Understanding the Difficulty of Training Transformers
For an education purpose, from-scratch, single-file, python-only pose-graph optimization implementation
codegen slam rotation jacobian gtsam gauss-newton pgo initialization pose-graph-optimization cholmod chordal-distance symforce
Next-generation google/wire with parallel dependency injection for Go
Reference caffe implementation of LSUV initialization
caffe deep-learning convolutional-networks convolutional-neural-networks initialization lsuv lsuv-initialization
Benchmark the init cost of Go packages
Simple implementation of the LSUV initialization in keras
keras convolutional-networks deeplearning convolutional-neural-networks initialization lsuv lsuv-initialization
Dependency injection a la carte
Simple implementation of the LSUV initialization in PyTorch
cnn pytorch convolutional-networks deeplearning convolutional-neural-networks initialization lsuv lsuv-initialization
[ISPRS JP&RS 2023] A Fast LiDAR Place Recognition and Localization Method by Fusing Local and Global Search
map navigation kalman-filtering kidnapped-vehicle lidar-point-cloud initialization global-localization lidar-localization map-based-localization
A framework for Open edX micro-frontend applications.
Class Normalization for Continual Zero-Shot Learning
The OpenMRS Initializer module is an API-only module that processes the content of the configuration folder when it is found inside OpenMRS' application data directory.
Initialize / Fill C++ array fast - O(1) time with only 1 extra bit of memory.
template library cpp paper array header bit data-structures header-only constant-time implementation initialization constant-space o1
The most flexible component-oriented framework for GoLang applications
Compile-time Dependency Injection for Go
This is the open source of my first paper 《Object-Aware SLAM Based on Efficient Quadric Initialization and Joint Data Association》, which has been accepted by RA-L & IROS 2022.
Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset.
keras mathematics rnn mathematics-machine-learning neuralnetworks orthogonal initialization dynamical-isometry
Short description for quick search
tensorflow dropout batch-normalization momentum softmax-regression l2-regularization rmsprop adam-optimizer mini-batch-gradient-descent bias-correction initialization gradient-check exponentially-weighted-averages learning-rate-decay
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