"Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification" Benedict Aaron Tjandra, Federico Barbero, @mmbronstein.bsky.social
#graphneuralnetworks
#graphneuralnetworks
November 21, 2024 at 11:03 AM
"Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification" Benedict Aaron Tjandra, Federico Barbero, @mmbronstein.bsky.social
#graphneuralnetworks
#graphneuralnetworks
"Graph Low-Rank Adapters of High Regularity for Graph Neural Networks and Graph Transformers" by PantelisPapageorgiou, Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, @mmbronstein.bsky.social
Paper: openreview.net/forum?id=gxh...
Code: github.com/PanPapag/GCo...
#graphneuralnetworks
Paper: openreview.net/forum?id=gxh...
Code: github.com/PanPapag/GCo...
#graphneuralnetworks
April 5, 2025 at 11:04 AM
"Graph Low-Rank Adapters of High Regularity for Graph Neural Networks and Graph Transformers" by PantelisPapageorgiou, Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, @mmbronstein.bsky.social
Paper: openreview.net/forum?id=gxh...
Code: github.com/PanPapag/GCo...
#graphneuralnetworks
Paper: openreview.net/forum?id=gxh...
Code: github.com/PanPapag/GCo...
#graphneuralnetworks
"Towards Quantifying Long-Range Interactions in Graph Maine Learning: a Large Graph Dataset and a Measurement" by Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, @mmbronstein.bsky.social, Xiaowen Dong
Paper: arxiv.org/abs/2503.09008
#graphneuralnetworks #machinelearning
Paper: arxiv.org/abs/2503.09008
#graphneuralnetworks #machinelearning
March 28, 2025 at 9:29 AM
"Towards Quantifying Long-Range Interactions in Graph Maine Learning: a Large Graph Dataset and a Measurement" by Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, @mmbronstein.bsky.social, Xiaowen Dong
Paper: arxiv.org/abs/2503.09008
#graphneuralnetworks #machinelearning
Paper: arxiv.org/abs/2503.09008
#graphneuralnetworks #machinelearning
💻 Code: github.com/PedrV/gnn-uq...
📄 Preprint: arxiv.org/abs/2605.22593
Co-authored w/ @pedrocvieira.bsky.social & Pedro Ribeiro.
#MachineLearning #GraphNeuralNetworks #DeepLearning #UncertaintyQuantification #GeometricDeepLearning
📄 Preprint: arxiv.org/abs/2605.22593
Co-authored w/ @pedrocvieira.bsky.social & Pedro Ribeiro.
#MachineLearning #GraphNeuralNetworks #DeepLearning #UncertaintyQuantification #GeometricDeepLearning
GitHub - PedrV/gnn-uq-inspector
Contribute to PedrV/gnn-uq-inspector development by creating an account on GitHub.
github.com
May 25, 2026 at 11:15 AM
💻 Code: github.com/PedrV/gnn-uq...
📄 Preprint: arxiv.org/abs/2605.22593
Co-authored w/ @pedrocvieira.bsky.social & Pedro Ribeiro.
#MachineLearning #GraphNeuralNetworks #DeepLearning #UncertaintyQuantification #GeometricDeepLearning
📄 Preprint: arxiv.org/abs/2605.22593
Co-authored w/ @pedrocvieira.bsky.social & Pedro Ribeiro.
#MachineLearning #GraphNeuralNetworks #DeepLearning #UncertaintyQuantification #GeometricDeepLearning
🤖 New method enhances explainability of Temporal Graph Networks
Researchers have developed a method to attribute predictions in Temporal Graph Networks through topology attribution trees and memory backtracking,...
#GraphNeuralNetworks #DeepLearning #PredictiveModels #AI #AIPulse
Researchers have developed a method to attribute predictions in Temporal Graph Networks through topology attribution trees and memory backtracking,...
#GraphNeuralNetworks #DeepLearning #PredictiveModels #AI #AIPulse
Read the full article →
www.synestesia.uk
July 10, 2026 at 9:34 AM
🤖 New method enhances explainability of Temporal Graph Networks
Researchers have developed a method to attribute predictions in Temporal Graph Networks through topology attribution trees and memory backtracking,...
#GraphNeuralNetworks #DeepLearning #PredictiveModels #AI #AIPulse
Researchers have developed a method to attribute predictions in Temporal Graph Networks through topology attribution trees and memory backtracking,...
#GraphNeuralNetworks #DeepLearning #PredictiveModels #AI #AIPulse
Graph Neural Networks Do Not Always Oversmooth" by Bastian Epping, Alexandre René, Moritz Helias, and Michael Schaub
Paper: arxiv.org/abs/2406.02269
#graphneuralnetworks
Paper: arxiv.org/abs/2406.02269
#graphneuralnetworks
November 25, 2024 at 1:24 PM
Graph Neural Networks Do Not Always Oversmooth" by Bastian Epping, Alexandre René, Moritz Helias, and Michael Schaub
Paper: arxiv.org/abs/2406.02269
#graphneuralnetworks
Paper: arxiv.org/abs/2406.02269
#graphneuralnetworks
🤖 Domain knowledge boosts ECG recognition model accuracy
Incorporating domain expertise into AI models improves their performance on electrocardiograph (ECG) recognition tasks, particularly for rare categories. A recent...
#GraphNeuralNetworks #DeepLearning #MedicalImaging #AI #AIPulse
Incorporating domain expertise into AI models improves their performance on electrocardiograph (ECG) recognition tasks, particularly for rare categories. A recent...
#GraphNeuralNetworks #DeepLearning #MedicalImaging #AI #AIPulse
Read the full article →
www.synestesia.uk
July 4, 2026 at 11:38 AM
🤖 Domain knowledge boosts ECG recognition model accuracy
Incorporating domain expertise into AI models improves their performance on electrocardiograph (ECG) recognition tasks, particularly for rare categories. A recent...
#GraphNeuralNetworks #DeepLearning #MedicalImaging #AI #AIPulse
Incorporating domain expertise into AI models improves their performance on electrocardiograph (ECG) recognition tasks, particularly for rare categories. A recent...
#GraphNeuralNetworks #DeepLearning #MedicalImaging #AI #AIPulse
Join us today at #NeurIPS2024 for our poster presentation:
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
📣 Can we go beyond state-of-the-art message-passing models based on spherical tensors such as #MACE and #NequIP?
Our #NeurIPS2024 paper explores higher-rank irreducible Cartesian tensors to design equivariant #MLIPs.
Paper: arxiv.org/abs/2405.14253
Code: github.com/nec-research...
Our #NeurIPS2024 paper explores higher-rank irreducible Cartesian tensors to design equivariant #MLIPs.
Paper: arxiv.org/abs/2405.14253
Code: github.com/nec-research...
December 11, 2024 at 3:38 PM
Join us today at #NeurIPS2024 for our poster presentation:
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
🤖 AI Security Framework Unveiled to Tackle Diverse Agentic Systems
Researchers are developing unified security evaluation methods for agentic AI systems, addressing the growing need for comprehensive risk...
#Benchmarking #GenerativeAI #GraphNeuralNetworks #AI #AIPulse
Researchers are developing unified security evaluation methods for agentic AI systems, addressing the growing need for comprehensive risk...
#Benchmarking #GenerativeAI #GraphNeuralNetworks #AI #AIPulse
Read the full article →
www.synestesia.uk
June 24, 2026 at 6:39 AM
🤖 AI Security Framework Unveiled to Tackle Diverse Agentic Systems
Researchers are developing unified security evaluation methods for agentic AI systems, addressing the growing need for comprehensive risk...
#Benchmarking #GenerativeAI #GraphNeuralNetworks #AI #AIPulse
Researchers are developing unified security evaluation methods for agentic AI systems, addressing the growing need for comprehensive risk...
#Benchmarking #GenerativeAI #GraphNeuralNetworks #AI #AIPulse
I'm excited to share that our paper, "Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance," has been accepted to NeurIPS 2024! 🎉
#NeurIPS #MARL #AI #ReinforcementLearning #MachineLearning #Equivariance #GraphNeuralNetworks
#NeurIPS #MARL #AI #ReinforcementLearning #MachineLearning #Equivariance #GraphNeuralNetworks
December 6, 2024 at 3:20 PM
I'm excited to share that our paper, "Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance," has been accepted to NeurIPS 2024! 🎉
#NeurIPS #MARL #AI #ReinforcementLearning #MachineLearning #Equivariance #GraphNeuralNetworks
#NeurIPS #MARL #AI #ReinforcementLearning #MachineLearning #Equivariance #GraphNeuralNetworks
🤖 AI Financial Oversight Tools Gain Traction in Regulated Markets
Financial regulators are increasingly adopting AI powered oversight tools to monitor and manage credit risks in decentralized finance. A new system,...
#PredictiveModels #GraphNeuralNetworks #AIInference #AI #AIPulse
Financial regulators are increasingly adopting AI powered oversight tools to monitor and manage credit risks in decentralized finance. A new system,...
#PredictiveModels #GraphNeuralNetworks #AIInference #AI #AIPulse
Read the full article →
www.synestesia.uk
June 21, 2026 at 2:31 AM
🤖 AI Financial Oversight Tools Gain Traction in Regulated Markets
Financial regulators are increasingly adopting AI powered oversight tools to monitor and manage credit risks in decentralized finance. A new system,...
#PredictiveModels #GraphNeuralNetworks #AIInference #AI #AIPulse
Financial regulators are increasingly adopting AI powered oversight tools to monitor and manage credit risks in decentralized finance. A new system,...
#PredictiveModels #GraphNeuralNetworks #AIInference #AI #AIPulse
🤖 Visual Graph Scaffolds for Structural Reasoning in Large Language Models
Researchers are increasingly exploring the use of visual graph structures to enhance the reasoning capabilities of large language models, finding that...
#GraphNeuralNetworks #DeepLearning #GenerativeAI #AIPulse
Researchers are increasingly exploring the use of visual graph structures to enhance the reasoning capabilities of large language models, finding that...
#GraphNeuralNetworks #DeepLearning #GenerativeAI #AIPulse
Read the full article →
www.synestesia.uk
June 3, 2026 at 12:30 PM
🤖 Visual Graph Scaffolds for Structural Reasoning in Large Language Models
Researchers are increasingly exploring the use of visual graph structures to enhance the reasoning capabilities of large language models, finding that...
#GraphNeuralNetworks #DeepLearning #GenerativeAI #AIPulse
Researchers are increasingly exploring the use of visual graph structures to enhance the reasoning capabilities of large language models, finding that...
#GraphNeuralNetworks #DeepLearning #GenerativeAI #AIPulse
🤖 Physics-inspired method improves attribution in complex systems
Researchers are increasingly using physics inspired methods to improve attribution accuracy in complex cyber physical systems. A recent framework,...
#PhysicsInformedAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Researchers are increasingly using physics inspired methods to improve attribution accuracy in complex cyber physical systems. A recent framework,...
#PhysicsInformedAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Read the full article →
www.synestesia.uk
July 8, 2026 at 6:38 PM
🤖 Physics-inspired method improves attribution in complex systems
Researchers are increasingly using physics inspired methods to improve attribution accuracy in complex cyber physical systems. A recent framework,...
#PhysicsInformedAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Researchers are increasingly using physics inspired methods to improve attribution accuracy in complex cyber physical systems. A recent framework,...
#PhysicsInformedAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Just published a new blog on 🎱 Pooling in #GraphNeuralNetworks!
💡Learn the fundamentals through this gentle introduction and discover how they can improve your GNN applications.
👉 Check it out here: gnn-pooling.notion.site
#GNN #MachineLearning #AI
💡Learn the fundamentals through this gentle introduction and discover how they can improve your GNN applications.
👉 Check it out here: gnn-pooling.notion.site
#GNN #MachineLearning #AI
1/3 - Pooling in Graph Neural Networks
November 2024
gnn-pooling.notion.site
December 19, 2024 at 3:51 PM
Just published a new blog on 🎱 Pooling in #GraphNeuralNetworks!
💡Learn the fundamentals through this gentle introduction and discover how they can improve your GNN applications.
👉 Check it out here: gnn-pooling.notion.site
#GNN #MachineLearning #AI
💡Learn the fundamentals through this gentle introduction and discover how they can improve your GNN applications.
👉 Check it out here: gnn-pooling.notion.site
#GNN #MachineLearning #AI
🤖 Graphify enables offline Python codebase analysis
Graphify allows for fully offline analysis of Python codebases, turning them into knowledge graphs without needing an API key or LLM backend. This capability was...
#AIInference #GraphNeuralNetworks #OperationalEfficiency #AI #AIPulse
Graphify allows for fully offline analysis of Python codebases, turning them into knowledge graphs without needing an API key or LLM backend. This capability was...
#AIInference #GraphNeuralNetworks #OperationalEfficiency #AI #AIPulse
Read the full article →
www.synestesia.uk
June 24, 2026 at 10:37 AM
🤖 Graphify enables offline Python codebase analysis
Graphify allows for fully offline analysis of Python codebases, turning them into knowledge graphs without needing an API key or LLM backend. This capability was...
#AIInference #GraphNeuralNetworks #OperationalEfficiency #AI #AIPulse
Graphify allows for fully offline analysis of Python codebases, turning them into knowledge graphs without needing an API key or LLM backend. This capability was...
#AIInference #GraphNeuralNetworks #OperationalEfficiency #AI #AIPulse
🤖 New Stability Theory for Tree-Structured Dissimilarity Matrices
Researchers have developed an ℓ0 type stability theory for tree structured dissimilarity matrices, showing that sparse edits propagate only through...
#DeepLearning #GraphNeuralNetworks #AIInference #AI #AIPulse
Researchers have developed an ℓ0 type stability theory for tree structured dissimilarity matrices, showing that sparse edits propagate only through...
#DeepLearning #GraphNeuralNetworks #AIInference #AI #AIPulse
Read the full article →
www.synestesia.uk
August 6, 2026 at 4:39 PM
🤖 New Stability Theory for Tree-Structured Dissimilarity Matrices
Researchers have developed an ℓ0 type stability theory for tree structured dissimilarity matrices, showing that sparse edits propagate only through...
#DeepLearning #GraphNeuralNetworks #AIInference #AI #AIPulse
Researchers have developed an ℓ0 type stability theory for tree structured dissimilarity matrices, showing that sparse edits propagate only through...
#DeepLearning #GraphNeuralNetworks #AIInference #AI #AIPulse
🤖 Hierarchical learning architecture boosts autonomous UAV swarm capabilities
Researchers have developed a novel three level hierarchical learning architecture that significantly enhances the autonomy and coordination of UAV...
#GraphNeuralNetworks #DeepLearning #Robotics #AI #AIPulse
Researchers have developed a novel three level hierarchical learning architecture that significantly enhances the autonomy and coordination of UAV...
#GraphNeuralNetworks #DeepLearning #Robotics #AI #AIPulse
Read the full article →
www.synestesia.uk
July 17, 2026 at 12:36 PM
🤖 Hierarchical learning architecture boosts autonomous UAV swarm capabilities
Researchers have developed a novel three level hierarchical learning architecture that significantly enhances the autonomy and coordination of UAV...
#GraphNeuralNetworks #DeepLearning #Robotics #AI #AIPulse
Researchers have developed a novel three level hierarchical learning architecture that significantly enhances the autonomy and coordination of UAV...
#GraphNeuralNetworks #DeepLearning #Robotics #AI #AIPulse
🤖 Causal-Audit Framework Boosts Large Language Model Reasoning
Researchers are increasingly adopting explicit causal reasoning frameworks to improve the reliability and interpretability of large language models in context...
#GraphNeuralNetworks #DeepLearning #AIInference #AI #AIPulse
Researchers are increasingly adopting explicit causal reasoning frameworks to improve the reliability and interpretability of large language models in context...
#GraphNeuralNetworks #DeepLearning #AIInference #AI #AIPulse
Read the full article →
www.synestesia.uk
July 20, 2026 at 7:32 PM
🤖 Causal-Audit Framework Boosts Large Language Model Reasoning
Researchers are increasingly adopting explicit causal reasoning frameworks to improve the reliability and interpretability of large language models in context...
#GraphNeuralNetworks #DeepLearning #AIInference #AI #AIPulse
Researchers are increasingly adopting explicit causal reasoning frameworks to improve the reliability and interpretability of large language models in context...
#GraphNeuralNetworks #DeepLearning #AIInference #AI #AIPulse
🤖 Hierarchical context retrieval boosts LLM performance
Large language models perform better on hierarchical and relational reasoning tasks when they retrieve context from structured knowledge graphs rather than flat...
#GenerativeAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Large language models perform better on hierarchical and relational reasoning tasks when they retrieve context from structured knowledge graphs rather than flat...
#GenerativeAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Read the full article →
www.synestesia.uk
July 17, 2026 at 8:38 PM
🤖 Hierarchical context retrieval boosts LLM performance
Large language models perform better on hierarchical and relational reasoning tasks when they retrieve context from structured knowledge graphs rather than flat...
#GenerativeAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
Large language models perform better on hierarchical and relational reasoning tasks when they retrieve context from structured knowledge graphs rather than flat...
#GenerativeAI #GraphNeuralNetworks #DeepLearning #AI #AIPulse
🤖 Graph Neural Networks Spread Beyond Research
Researchers are increasingly applying graph neural networks to real world problems like urban planning and video generation. A recent tutorial demonstrates an end to...
#GraphNeuralNetworks #GenerativeAI #DeepLearning #AI #AIPulse
Researchers are increasingly applying graph neural networks to real world problems like urban planning and video generation. A recent tutorial demonstrates an end to...
#GraphNeuralNetworks #GenerativeAI #DeepLearning #AI #AIPulse
Read the full article →
www.synestesia.uk
June 14, 2026 at 11:31 AM
🤖 Graph Neural Networks Spread Beyond Research
Researchers are increasingly applying graph neural networks to real world problems like urban planning and video generation. A recent tutorial demonstrates an end to...
#GraphNeuralNetworks #GenerativeAI #DeepLearning #AI #AIPulse
Researchers are increasingly applying graph neural networks to real world problems like urban planning and video generation. A recent tutorial demonstrates an end to...
#GraphNeuralNetworks #GenerativeAI #DeepLearning #AI #AIPulse
🚨 New Course Alert! 🚨
#MachineLearning for #DrugDiscovery | 12–15 Oct 2026 | Online
Learn ML, deep learning & graph neural networks for drug discovery with hands-on #PyTorch exercises. 🌐
www.physalia-courses.org/courses-work...
#DeepLearning #GraphNeuralNetworks #Bioinformatics
#MachineLearning for #DrugDiscovery | 12–15 Oct 2026 | Online
Learn ML, deep learning & graph neural networks for drug discovery with hands-on #PyTorch exercises. 🌐
www.physalia-courses.org/courses-work...
#DeepLearning #GraphNeuralNetworks #Bioinformatics
Machine Learning for Drug Discovery
12-15 October 2026
www.physalia-courses.org
April 8, 2026 at 2:59 PM
🚨 New Course Alert! 🚨
#MachineLearning for #DrugDiscovery | 12–15 Oct 2026 | Online
Learn ML, deep learning & graph neural networks for drug discovery with hands-on #PyTorch exercises. 🌐
www.physalia-courses.org/courses-work...
#DeepLearning #GraphNeuralNetworks #Bioinformatics
#MachineLearning for #DrugDiscovery | 12–15 Oct 2026 | Online
Learn ML, deep learning & graph neural networks for drug discovery with hands-on #PyTorch exercises. 🌐
www.physalia-courses.org/courses-work...
#DeepLearning #GraphNeuralNetworks #Bioinformatics
STRUCTURES YRC members Manuel Klockow and Peter Lippmann presented their work at ICLR 2026 in Rio de Janeiro, Brazil. (1/5)
#STRUCTURESHeidelberg #ICLR2026 #MachineLearning #DeepLearning #GraphNeuralNetworks #earlycareerResearcher#HeidelbergUniversity #ScientificMachineLearning
#STRUCTURESHeidelberg #ICLR2026 #MachineLearning #DeepLearning #GraphNeuralNetworks #earlycareerResearcher#HeidelbergUniversity #ScientificMachineLearning
May 29, 2026 at 12:34 PM
STRUCTURES YRC members Manuel Klockow and Peter Lippmann presented their work at ICLR 2026 in Rio de Janeiro, Brazil. (1/5)
#STRUCTURESHeidelberg #ICLR2026 #MachineLearning #DeepLearning #GraphNeuralNetworks #earlycareerResearcher#HeidelbergUniversity #ScientificMachineLearning
#STRUCTURESHeidelberg #ICLR2026 #MachineLearning #DeepLearning #GraphNeuralNetworks #earlycareerResearcher#HeidelbergUniversity #ScientificMachineLearning
Tenemos cita el 20 de febrero 🔥 Nos vemos en BBVA AI Factory para hablar embeddings para contratación financiera y de redes neuronales de grafos.
Estamos probando @guild.host, ¡reserva tu plaza aquí! 👇
guild.host/events/embed...
#PyData #PyDataMadrid #python #embeddings #GraphNeuralNetworks
Estamos probando @guild.host, ¡reserva tu plaza aquí! 👇
guild.host/events/embed...
#PyData #PyDataMadrid #python #embeddings #GraphNeuralNetworks
📄 Embeddings para contratación financiera & Redes neuronales de grafos | Guild
Feb 20th 7:00PM: PyData Madrid vuelve en febrero para hablar de Python, Datos, Visualización, Inteligencia Artificial, ¡Y lo que surja!
Est
guild.host
February 11, 2025 at 8:55 AM
Tenemos cita el 20 de febrero 🔥 Nos vemos en BBVA AI Factory para hablar embeddings para contratación financiera y de redes neuronales de grafos.
Estamos probando @guild.host, ¡reserva tu plaza aquí! 👇
guild.host/events/embed...
#PyData #PyDataMadrid #python #embeddings #GraphNeuralNetworks
Estamos probando @guild.host, ¡reserva tu plaza aquí! 👇
guild.host/events/embed...
#PyData #PyDataMadrid #python #embeddings #GraphNeuralNetworks
Paolo Bresolin presents his work at #BITS2026 on learning general-purpose embeddings from tumor phylogenetic trees using Graph Neural Networks.
#Bioinformatics #CancerResearch #GraphNeuralNetworks #TumorEvolution
#Bioinformatics #CancerResearch #GraphNeuralNetworks #TumorEvolution
May 28, 2026 at 10:14 AM
Paolo Bresolin presents his work at #BITS2026 on learning general-purpose embeddings from tumor phylogenetic trees using Graph Neural Networks.
#Bioinformatics #CancerResearch #GraphNeuralNetworks #TumorEvolution
#Bioinformatics #CancerResearch #GraphNeuralNetworks #TumorEvolution