Hyperbolic Learning Rate Scheduler
deep-learning image-classification time-series-forecasting operator-learning learning-rate-scheduler
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Updated
Aug 19, 2026 - Python
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learning-rate-scheduler
Here are 10 public repositories matching this topic...
This project modifies the classic VGG16 architecture to classify images into four distinct categories with high accuracy. It incorporates data augmentation, dynamic learning rate adjustments, and comprehensive performance evaluation using accuracy metrics and confusion matrices. Built with PyTorch and supported by a suite of powerful libraries
python machine-learning deep-learning numpy scikit-learn pil pytorch seaborn image-classification matplotlib vgg16 data-augmentation torchvision accuracy-evaluation learning-rate-scheduler
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Dec 11, 2023 - Python
Minimal PyTorch implementation of cosine annealing with warm-up for super-convergence training schedules.
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Jun 5, 2022 - Python
🖼️A PyTorch-based Convolutional Neural Network (CNN) built from scratch to classify CIFAR-10 images. Achieves 82.93% test accuracy using Batch Normalization, Dropout, Data Augmentation, and a ReduceLROnPlateau scheduler. Includes detailed evaluation curves, confusion matrices, and per-class analyses.
python machine-learning computer-vision deep-learning numpy sklearn jupyter-notebook cnn data-visualization pytorch seaborn artificial-intelligence batch-normalization neural-networks image-classification matplotlib convolutional-neural-networks data-augmentation cifar-10 learning-rate-scheduler
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Jul 24, 2026 - Jupyter Notebook
PyTorch implementation of the generalized Newton's method for learning rate selection
machine-learning pytorch artificial-intelligence neural-networks learning-rate newtons-method learning-rate-scheduling learning-rate-scheduler
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Feb 10, 2025 - Python
A comparative analysis of 4 optimizer/regularization configurations (Baseline SGD, SGD+Momentum, Adam+High Dropout, AdamW+Cosine Annealing) on a PyTorch deep neural network, with live experiment tracking via Weights & Biases.
python deep-learning optimizer pytorch dropout sgd regularization momentum adam adamw weights-and-biases learning-rate-scheduler
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Jul 27, 2026 - Python
Lightweight CNN for 28×28 grayscale multi-class image classification with augmentation & regularization.
computer-vision deep-learning cnn pytorch image-classification resnet regularization vgg16 augmentation ablation-study 64x64 28x28 learning-rate-scheduler
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Oct 7, 2025 - Jupyter Notebook
High-performance PyTorch LR schedulers with cosine annealing, flexible waypoints, plateau steps, and LR scaling. Unified API with pre-computed segments for zero runtime overhead.
training machine-learning deep-learning pytorch distributed-training cosine-annealing lr-scheduling learning-rate-scheduler waypoint-scheduler
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Oct 13, 2025 - Python
The Newton-like learning rate scheduler
machine-learning machine-learning-algorithms artificial-intelligence learning-rate second-order-optimization learning-rate-scheduler
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Apr 29, 2025 - Python
Learning-rate schedules from boundary-value constrained trust-region problems.
learning deep-learning optimizer energy-minimization step-size learning-rate-decay boundary-value-problem learning-rate-scheduling learning-rate-warmup trust-region-methods stochastic-gradient-method learning-rate-scheduler learning-rate-schedule
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Sep 8, 2026 - Python
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