Distributed Computing
ETH Zurich

Florian Grötschla

Florian Grötschla

Distributed Computing Group
Computer Engineering and Networks Laboratory (TIK)
Department Electrical Engineering (D-ITET)
Office ETZ G 63
ETH Zurich

Gloriastrasse 35
8092 Zurich
Switzerland

phone+41 44 63 24448
fax+41 44 63 21036
email

Publications

Theses & Labs

Available Theses & Labs

TitleTypeContact/SupervisorAssigned
Agent-based Graph Neural Networks with CommunicationM/SFlorian Grötschla,
Béni Egressy
available
Algorithmic Reasoning with Graph Neural NetworksSFlorian Grötschla,
Joël Mathys
available
Learning Finite State Automatons on Graphs with Reinforcement LearningM/SFlorian Grötschla,
Joël Mathys
available
Lyrics-to-Audio AlignmentSFlorian Grötschla,
Luca Lanzendörfer
available
Overlap Removal with Graph Neural NetworksSFlorian Grötschlaavailable

Current Theses & Labs

TitleTypeContact/SupervisorAssignedStudent(s)
AI + ArtSFlorian Grötschla,
Luca Lanzendörfer
HS 23
Audio Source Separation using Language ModelsSLuca Lanzendörfer,
Florian Grötschla
HS 23
Automated Electronic Placement and RoutingMFlorian Grötschla,
Benjamin Estermann
HS 23
Bring Your Own Idea: Music DatasetBLuca Lanzendörfer,
Florian Grötschla
HS 23
Exploring Activation Ensembles for Neural NetworksBFlorian Grötschla,
Joël Mathys
HS 23
GNNs for TPU Code GraphsSJoël Mathys,
Florian Grötschla
HS 23
Swarm Intelligence Reinforcement LearningMBenjamin Estermann,
Florian Grötschla
HS 23

Past Theses & Labs

TitleTypeContact/SupervisorAssignedStudent(s)
Enhancing GNNs: An Exploration of Iterative Solving and Augmentation TechniquesBJoël Mathys,
Florian Grötschla
FS 23
Asynchronous GNNs [confidential]GJoël Mathys,
Florian Grötschla
FS 23
DISCO-10M Creation and Data Exploration [confidential]SLuca Lanzendörfer,
Florian Grötschla
FS 23
Finite State Algorithm Learning on Graphs [confidential]MJoël Mathys,
Florian Grötschla
FS 23
SALSA-CLRS: A Sparse and Scalable Benchmark for Algorithmic Reasoning [confidential]SFlorian Grötschla,
Joël Mathys
FS 23
A Generalisation Benchmark for Machine Learning Methods Predicting Fluid Flows [confidential]BFlorian Grötschla,
Joël Mathys
FS 23
Swarm Intelligence Cup [confidential]GBenjamin Estermann,
Florian Grötschla
FS 23
Bitcoin Lightning Network Statistics and On-Chain Analysis [confidential]BFlorian Grötschla,
Lioba Heimbach
HS 22
Challenging Code Search Models through Semantic Attacks [confidential]SPeter Belcák,
Florian Grötschla
HS 22
Challenging the Lexical Focus of Code SearchSPeter Belcák,
Florian Grötschla
HS 22
Canonical Identifier Naming on Code Search ModelsGPeter Belcák,
Florian Grötschla
HS 22
Decentralized Federated Policy Gradient with Provably Fast Convergence and Byzantine Fault Tolerance [confidential]SXiaofeng Flint Fan,
Florian Grötschla
HS 22
Efficient Graph Drawing with GNNs using Overlay Graphs [confidential]BFlorian Grötschla,
Joël Mathys
HS 22
Exploring Graph Neural Networks and Hierarchical Structures for Traffic ForecastingBJoël Mathys,
Florian Grötschla
HS 22
SSA Data Flow Information for Semantic Code TasksBPeter Belcák,
Florian Grötschla
FS 22
Inconvenient Data Sets for Graph Neural Networks [confidential]BBéni Egressy,
Florian Grötschla
FS 22
Unreasonable Effectiveness of Edge Features: Formalization and Applications of Edge Pre-coloring in Color Refinement [confidential]SBéni Egressy,
Florian Grötschla
FS 22
Algorithm Learning from DataBPeter Belcák,
Florian Grötschla
FS 22
Benchmarking Graph Neural Network Models [confidential]SBéni Egressy,
Florian Grötschla
FS 22