Image-processing software for cryo-electron microscopy
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Updated
May 8, 2024 - C++
Image-processing software for cryo-electron microscopy
Demystify AI concepts: hand-solved problems translated into code for clarity.
A fast and flexible Structural Equation Modelling Framework
Analyze the customer data, build a neural network to help the operations team identify the customers that are more likely to churn, and provide recommendations on how to retain such customers
The study focuses on modeling and predicting H5N1 bird flu outbreaks in the United States at the county level, utilizing diverse statistical techniques and machine learning models.
A PyTorch implementation of DropGrad regularization for Federated Learning
Coding ML models, Sampling Methods, Feature Selection algorithms from scratch
Controlling the spectral norm of implicitly linear layers (e.g., convolutional layers)
Developed innovative optimization and ML algorithms to tackle data science tasks, including classification and sparse recovery, focusing on the NP-hard Maximum Feasible Subsystem problem.
Implemented logistic regression to classify microchips based on Quality Assurance (QA) test results for acceptance or rejection.
Implementation of SvF-technology of balanced identification of mathematical models by experimental data
The set of CPU/GPU optimised regularisation modules for iterative image reconstruction and other image processing tasks
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…
A Regular Programming Protocol (RP)!
Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.
Implementation of our ACL 2020 paper: Structured Tuning for Semantic Role Labeling
C++ library for Sorted L-One Penalized Estimation (SLOPE)
learning python day 12
Code for reproducing Manifold Mixup results (ICML 2019)
Official repository for the "Learned regularizations for multi-parameter elastic full waveform inversion using diffusion models" paper.
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