Philip Hierhager
phierhager
Machine Learning Researcher | Geometric DL & RL
Languages
Repos
32
Stars
10
Forks
1
Top Language
Python
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Top Repositories
Anomaly detection for network traffic with machine learning.
JAX-native Home Energy Management System (HEMS) simulation framework designed for high-performance control optimization and reinforcement learning.
Experimenting with Consensus-based optimization and sampling methods.
Researching on the impact of exponential noise on Consensus-based Optimization.
Writing a summary and evaluation of the PESNet paper.
Repositories
32No description provided.
Config-Driven RL & Game Theory in JAX
JAX-native Home Energy Management System (HEMS) simulation framework designed for high-performance control optimization and reinforcement learning.
Numerics experiments with Julia
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Influence of Noise on Quantum Variational Algorithms
Evaluation of Quantum-Classical Hybrid Solution Methods for 3SAT Problems
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Anomaly detection for network traffic with machine learning.
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DesignPatternGuide is an interactive, expert-level web application that helps Python developers select the most appropriate design patterns for their projects. It covers Creational, Structural, and Behavioral patterns, providing professional guidance, practical Python examples, and insights for scalable and maintainable code.
PyTypeGuide – Interactive expert-level tool to select the most suitable Python data types for your use case, with documentation links and professional recommendations.
Exploring Self-Supervised Learning for Efficient Perception in Autonomous Driving
Making BERT more efficient through weight sharing
Simulate Energy of Buildings using Machine Learning
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Experiments with Causality
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Exploration of the C language and tools.
Running federated learning for security
Working on MNIST dataset with discriminative and generative classifiers.
Experimenting with Consensus-based optimization and sampling methods.
Researching on the impact of exponential noise on Consensus-based Optimization.
Writing a summary and evaluation of the PESNet paper.
Exploring Machine Learning
No description provided.
Using evolutionary algorithms to optimize quantum circuits
Quantum & Classical Analysis of Insurance Claims