Contributors per cycle
Accepted projects each year, against the median organization that year
View as table
| mlpack | Median organization | |
|---|---|---|
| 2016 | 6 | 4 |
| 2017 | 10 | 4 |
| 2018 | 6 | 3 |
| 2019 | 9 | 4 |
| 2020 | 8 | 4 |
| 2021 | 8 | 4 |
| 2022 | 4 | 3 |
| 2023 | 3 | 4 |
| 2024 | 6 | 4 |
| 2025 | 0 | 5 |
| 2026 | 0 | 4 |
Last took part in 2024
mlpack
a fast, flexible machine learning library
Contributors in 2026
–
Not taking part
Projects since 2016
60
6.7 a cycle on average
Cycles
9 of 11
First in 2016
Rank in 2026
–
By contributors
Mentors
4
for 6 projects in 2024
Stack and topics
Each one has its own page of organizations and trends
Technologies
# Topics
Quick answers
- Is mlpack in GSoC 2026?
- No. It last took part in 2024.
- How long has it taken part?
- 9 of 11 cycles since 2016, first in 2016.
- How many contributors does it usually take?
- 6.7 a cycle on average, 60 in total. Its largest cycle was 2017, with 10.
- What does it build with?
- C++, Python, Machine learning, Deep Learning, Templates, OpenMP and 1 more.
Accepted projects
6 projects in 2024 · All 60 projects since 2016
Integrating Advanced CMA-ES Strategies into mlpack
benyMentored by Marcus Edel, Tarek Elsayed
This proposal seeks to enrich the mlpack library by incorporating advanced evolutionary strategies, specifically focusing on enhancing the Covariance...
Implementing XGBoost
Abhimanyu DayalMentored by Marcus Edel, Omar Shrit, Tarek Elsayed
The goal of this project is to finish the XGBoost implementation inside of mlpack, followed by intense tuning, profiling, and improving such that it...
Adding NSGA-3 and AGE-MOEA Multi Objective Optimizers
Satyam Govind ShuklaMentored by Marcus Edel, Omar Shrit
Multi-objective optimization (MOO) plays a crucial role in decision-making across diverse fields, where conflicting objectives need to be balanced....
Performance and Memory Optimization for Machine Learning Algorithms in mlpack
Mark FischingerMentored by Ryan Curtin, Omar Shrit
In Google Summer of Code 2024, I focused on optimizing key algorithms in the mlpack library, targeting both performance and memory usage across...
ONNX-mlpack converter
kumar utkarshMentored by Marcus Edel, Omar Shrit
Training intricate machine learning models to achieve the desired level of proficiency can be time-consuming and require high computational...
Implementing yolov3-tiny in mlpack
Andrew FureyMentored by Omar Shrit, Tarek Elsayed
I will implement the yolov3-tiny model using mlpack. I will get Darknet-19 working, flesh out the API, build and train yolov3-tiny, publish the...
Activation functions and Pooling methods
Mayank RajMentored by Marcus Edel, Abhinav Anand
Two new activation functions have been recently proposed FTSwish, and LiSHT and I am proposing to add them to mlpack along with two Pooling methods....
Enhance CMA-ES
SuvarshMentored by Marcus Edel
Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is an evolutionary strategy which updates the covariance matrix of a normal search...
Expanding Reinforcement Learning in mlpack: DDPG and TD3 Agents Integration
Tarek ElsayedMentored by Marcus Edel, Shubham Agrawal
This project's primary objective was to enrich the mlpack reinforcement learning framework by incorporating new agents, specifically DDPG and TD3,...
Enhance CMA-ES from existing implementation in ensmallen - a optimization header library
John HoangMentored by Marcus Edel
The project proposes to enhance the existing mlpack CMA-ES (Covariance matrix adaption-evolutionary strategy) implementation. From the outdated...
Ready to use Models
Shubham AgrawalMentored by Ryan Curtin, Kartik Dutt, Jeffin Sam
The aim is to implement various pre-trained models ranging from very basic AlexNet to super complex networks, including implementing different layers...
Example Zoo
Tarek ElsayedMentored by Marcus Edel, Kartik Dutt
Example Zoo is an implementation of mlpack showcasing its potential usage in the real-world domain. It will provide a better starting point for new...
Addition of PPO, Twin Delayed DDPG, Hindsight Experience Replay to RL Codebase
Eshaan AgarwalMentored by Marcus Edel, Sai, Mohd Fauz
After comparing various algorithms and brainstorming about their methods of implementation, I came up with the Twin Delayed DDPG (TD3) Fujimoto et....
Replacing boost spirits
Gopi Manohar TatirajuMentored by Omar Shrit
The project revolves around reducing the binary footprint of mlpack by replacing the functionality of boost::spirits to handle a more diverse range...
A Framework for Multiobjective Optimizers
Nanubala Gnana SaiMentored by James Balamuta, Sayan Goswami, Marcus Edel
The mlpack library boasts an extensive set of objective optimizers, almost all of which focus on single-objective problems. Previous works by Sayan...
Example Zoo
Roshan SwainMentored by Kartik Dutt, Marcus Edel
Example Zoo is an implementation of mlpack showcasing its potential usage in the real-world domain. It will provide a better starting point for new...
Revamp mlpack bindings
Nippun SharmaMentored by Ryan Curtin, James Balamuta, Yashwant Singh Parihar
The project proposes to revamp the existing mlpack bindings. Mlpack is one of the most flexible machine learning libraries when accessed through C++...
Improvisation and Implementation of ANN Modules
Abhinav AnandMentored by Marcus Edel
Adding new layers (Upsample, Group Normalization and ChannelShuffle) to the ANN module of mlpack. Improve the speed of pooling operations of max,...
Improve Tree Ensemble Support
Rishabh GargMentored by gman, Ryan Curtin
Tree ensembles are arguably the best class of machine learning algorithms out there. They regularly win competitive data science competitions. This...
Ready to use Models in mlpack
Aakash KaushikMentored by Kartik Dutt, Marcus Edel
Is to implement MobileNetV1 which will also include implementing depthwise separable convolutions and a resnet model builder that can be used to...
Example Zoo
David Port LouisMentored by Kartik Dutt, Marcus Edel
Example Zoo provides starters a glimpse of most if not all features provided by mlpack, such that users can run the code for themselves to see it in...
mlpack on RPi and other resource-constrained devices
Omar ShritMentored by Roberto Hueso Gómez, Ryan Curtin
The objective of this project is to minimize mlpack library algorithms to fit into resource constrained devices such as Raspberry PI, Arduino, or...
Improvisation and Implementation of ANN Modules
Anjishnu MukherjeeMentored by Sreenik Seal
In this project, my goal is to update the existing ANN facilities within mlpack and the deliverable is an improved ANN module. This includes adding...
Visualization Tool
Jeffin SamMentored by Ryan Birmingham, Toshal Agrawal
Working with mlpack for almost a year was great. I have always been a fan of the concept see and do. If we can see a graph plotting the accuracy...
Application of ANN Algorithms Implemented in mlpack.
Kartik DuttMentored by Sangyeon Kim, Saksham Bansal
Over the course of the last couple of years, Computer Vision has played a crucial role in the field of Deep Learning. Object detection is one of the...
Implementing Essential Deep Learning Module
Himanshu PathakMentored by Saksham Bansal
In this project, I am trying to implement some deep learning modules which are used for classification. I am trying to implement some important...
Addition of Rainbow and Soft Actor-Critic to RL codebase
Nishant KumarMentored by Rahul Prabhu, Marcus Edel
After comparing various algorithms and brainstorming about their methods of implementation, I came up with the Rainbow Hessel et al., 2017 and Soft...
Transformer and BERT in mlpack
Mrityunjay TripathiMentored by Mikhail Lozhnikov
Connecting the encoder and decoder through an attention mechanism has made some of the best translation models. The encoder encodes input sentences...
Automatically-Generated R Bindings
Yashwant Singh PariharMentored by Ryan Curtin, James Balamuta, Dirk Eddelbuettel
R is a programming language with a design focused on simplicity, effectiveness and performance, that is widely used in all kind of projects. With...
Application of ANN Algorithms Implemented in mlpack
Mehul Kumar NiralaMentored by Sumedh Ghaisas, Marcus Edel
Application of ANN algorithms implemented in mlpack. Implementation of VGG 19 for Image Classification. LSTM Networks for Sentiment Analysis. LSTM...
String Processing Utilities
Jeffin SamMentored by Mikhail Lozhnikov
To develop String Processing Utilities for boosting mlpack library to manipulate string data types and to convert it into numeric datatype to apply...
mlpack-Tensorflow Translator
Sreenik SealMentored by Atharva Khandait
The purpose of this project is to build a converter that can translate models built in Tensorflow, Keras, Pytorch, Mxnet, ONNX to mlpack's model...
Implementing Essential Deep Learning Modules
Saksham BansalMentored by Shikhar Jaiswal
In recent years, generative adversarial networks have proven to be very effective for training generative models and hundreds of different variants...
Quantum Gaussian Mixture Models
Sangyeon KimMentored by Sumedh Ghaisas
Gaussian Mixture Model (GMM) is widely used in computer vision as a state-of-the-art clustering algorithm. This project proposes Quantum Gaussian...
PPO(Proximal Policy Optimization)
xiaohong jiMentored by Manish Kumar, Marcus Edel
A new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment,...
Implementing Essential Deep Learning Modules
Toshal AgrawalMentored by Shikhar Jaiswal
Various Deep learning architectures such as deep neural networks and recurrent neural networks are applied to fields including computer vision,...
NeuroEvolution of Augmenting Topologies & Multi-Objective Optimization
Rahul Ganesh PrabhuMentored by Manish Kumar, Marcus Edel
NeuroEvolution of Augmenting Toplogies (NEAT) is a genetic algorithm that can evolve networks of unbound complexity by starting from simple networks...
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Advanced Kernel Density Estimation Improvements
Roberto Hueso GomezMentored by Ryan Curtin
Kernel Density Estimation (KDE) is a widely used non-parametric technique to estimate a probability density function. mlpack already had an...
LMNN (via Low-Rank optimization) & BoostMetric Implementation
Manish KumarMentored by Ryan Curtin
Many cognitive techniques, such as recognition and categorization are assumed to have need of establishing similarities between perceptual or...
Neural Collaborative Filtering
Haritha Sreedharan NairMentored by Marcus Edel
Recommendation systems are widely used in various online and offline platforms, collaborative filtering being the most commonly used method for...
Alternatives to Neighborhood-Based Collaborative Filtering
Wenhao HuangMentored by Mikhail Lozhnikov
The overall objective of this project is to improve the current CF module in mlpack to provide better rating prediciton, fast execution, and flexible...
Automated Binding Generator
Yasmine DumouchelMentored by Kevin Avignon, Ryan Curtin
This automatically-generated Go binding proposal aims to allow Go users to have access to the fast and scalable machine learning library that is...
Variational Autoencoders
Atharva KhandaitMentored by Sumedh Ghaisas
Variational Autoencoders(VAEs) are widely used in unsupervised learning of complicated distributions. The more classical generative models depend...
Implementing Essential Deep Learning Modules
Shikhar JaiswalMentored by Marcus Edel
Over the years, Deep Learning has become a promising field of work, attracting attention from the most prominent Machine Learning researchers of the...
Neural Turing Machines
Sumedh GhaisasMentored by Ryan Curtin, Marcus Edel
One of the gems dug up by Deep Mind in the field of neural learning is Neural Turing Machines. By extending the capabilities of a simple neural...
Neural Evolution Algorithms on NES games
KARTIK NIGHANIAMentored by Marcus Edel
The goal of my project is to implement multiple neural evolution algorithms ie. ● NEAT - Neural Evolution through Augmented Topologies ● Hyper-NEAT -...
Deep Learning Modules
Kris SinghMentored by Mikhail Lozhnikov
Implementation of RBM, ssRBM, GAN and stacked GAN
GSoC '17 "Augmented RNNs" project proposal
Konstantin SidorovMentored by Ryan Curtin, Marcus Edel
I am applying to work on the GSoC 2017 Augmented RNNs project. I am currently a first-year Software Engineering student from Astrakhan State...
Reinforcement Learning Framework
Shangtong ZhangMentored by Marcus Edel
This projects will implement a framework for double deep Q-Learning and some asynchronous methods for DeepRL including asynchronous one-step...
Cross-Validation and Hyper-Parameter Tuning
Kirill MishchenkoMentored by Ryan Curtin
Solving a problem with machine learning algorithms is often a tedious process that requires many experiments before things start to work. The project...
GSoC-2017: Build testing with Docker and VMs
Saurabh GuptaMentored by Ryan Curtin
The objectives of the project are as: Completing the build matrix - testing on different compilers, different architectures, different Boost...
Frank-Wolfe Algorithm for Sparse Optimization and Regularization of Atom Norms
Chenzhe DiaoMentored by stephentu
It is known in Jaggi's paper that the traditional OMP algorithm for sparse optimization problems could fit into FW type algorithm. This generalized...
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Parallel stochastic optimization methods
Shikhar BhardwajMentored by Yannis Mentekidis
The free lunch is over and with the ever increasing amounts of data to be analyzed and processed by learning algorithms, we need to find methods for...
Better Benchmarking for mlpack Libraries
Dewang SultaniaMentored by Ryan Curtin, Marcus Edel
There are many mlpack methods that have been added since the previous benchmarking system was build and they need to be benchmarked. These include...
We need to go deeper - GoogLeNet
nilay_jainMentored by Marcus Edel, Tham
To implement the components of the GoogLeNet architecture (the inception layer, global average pooling, and other pieces), and then build GoogLeNet...
Approximate Nearest Neighbor Search: Implementation of Multiprobe LSH and LSH Tuning
mentekidMentored by Ryan Curtin
Approximate Nearest Neighbor Search solutions become appealing in problems where dimensionality increases. Locality Sensitive Hashing is a popular...
Neuroevolution Algorithms Implementation
BangMentored by Marcus Edel
Neuroevolution algorithms search optimal solutions by evolution rather than learning, which enables them to deal with large complex problems. In this...
Approximate Nearest Neighbor Search
Marcos PividoriMentored by sumedhghaisas
Mlpack provides an extensible, flexible exact nearest neighbor search implementation, with the ability to do dual-tree k-NN search. However, there is...
Dataset and Experimentation Tools
KeonKimMentored by Tham
This GSoC project aims to develop a tool for managing dataset and experimenting the data. This project is important because most of the time used...
R+ trees, Hilbert R trees, vantage point trees, random projection trees, UB trees implementation
lozhnikovMentored by Ryan Curtin
Many methods of the mlpack machine learning library (such as nearest neighbor search, range search and others) are based on dual-tree algorithms...
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Claim your projectMachine Learning for Science (ML4SCI)
33 contributors in 2026 · 6 cycles
Ste||ar group
4 contributors in 2026 · 10 cycles
NumFOCUS
27 contributors in 2026 · 11 cycles
CERN-HSF
26 contributors in 2026 · 10 cycles
Data: Google Summer of Code public archive. Contributor counts are accepted projects.