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09/02/2023
A 3D explainability framework to uncover learning patterns and crucial sub-regions in variable sulci recognition
Precisely identifying sulcal features in brain MRI is made challenging b...
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08/23/2023
Graph Neural Stochastic Differential Equations
We present a novel model Graph Neural Stochastic Differential Equations ...
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08/23/2023
Will More Expressive Graph Neural Networks do Better on Generative Tasks?
Graph generation poses a significant challenge as it involves predicting...
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08/21/2023
Topological Graph Signal Compression
Recently emerged Topological Deep Learning (TDL) methods aim to extend c...
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07/18/2023
Neural Priority Queues for Graph Neural Networks
Graph Neural Networks (GNNs) have shown considerable success in neural a...
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07/01/2023
SHARCS: Shared Concept Space for Explainable Multimodal Learning
Multimodal learning is an essential paradigm for addressing complex real...
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06/08/2023
Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs
Graphs are widely used to encapsulate a variety of data formats, but rea...
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06/08/2023
Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models
Tabular data is often hidden in text, particularly in medical diagnostic...
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06/07/2023
Neural Embeddings for Protein Graphs
Proteins perform much of the work in living organisms, and consequently ...
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06/06/2023
Graph Classification Gaussian Processes via Spectral Features
Graph classification aims to categorise graphs based on their structure ...
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06/06/2023
CIN++: Enhancing Topological Message Passing
Graph Neural Networks (GNNs) have demonstrated remarkable success in lea...
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06/02/2023
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-Resolution
Reference-based super-resolution (RefSR) has gained considerable success...
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06/01/2023
Renormalized Graph Neural Networks
Graph Neural Networks (GNNs) have become essential for studying complex ...
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05/30/2023
Group Invariant Global Pooling
Much work has been devoted to devising architectures that build group-eq...
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05/24/2023
Multi-State RNA Design with Geometric Multi-Graph Neural Networks
Computational RNA design has broad applications across synthetic biology...
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05/18/2023
Neural Algorithmic Reasoning for Combinatorial Optimisation
Solving NP-hard/complete combinatorial problems with neural networks is ...
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05/17/2023
Deep Multiple Instance Learning with Distance-Aware Self-Attention
Traditional supervised learning tasks require a label for every instance...
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05/15/2023
Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing
Recently, Koopman operator theory has become a powerful tool for develop...
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04/27/2023
Categorical Foundations of Explainable AI
Explainable AI (XAI) aims to address the human need for safe and reliabl...
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04/27/2023
Interpretable Neural-Symbolic Concept Reasoning
Deep learning methods are highly accurate, yet their opaque decision pro...
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04/16/2023
Assisting clinical practice with fuzzy probabilistic decision trees
The need for fully human-understandable models is increasingly being rec...
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04/11/2023
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing
Although neural networks (especially deep neural networks) have achieved...
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04/07/2023
Sheaf Neural Networks for Graph-based Recommender Systems
Recent progress in Graph Neural Networks has resulted in wide adoption b...
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04/06/2023
ElegansNet: a brief scientific report and initial experiments
This research report introduces ElegansNet, a neural network that mimics...
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03/06/2023
HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN
In this paper have developed a novel hybrid hierarchical attention-based...
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02/22/2023
A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuning
Super-resolution plays an essential role in medical imaging because it p...
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02/15/2023
A Federated Learning Benchmark for Drug-Target Interaction
Aggregating pharmaceutical data in the drug-target interaction (DTI) dom...
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02/09/2023
GCI: A (G)raph (C)oncept (I)nterpretation Framework
Explainable AI (XAI) underwent a recent surge in research on concept ext...
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02/06/2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Message Passing Neural Networks (MPNNs) are instances of Graph Neural Ne...
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02/02/2023
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
Graph Neural Networks (GNNs) have become the leading paradigm for learni...
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01/26/2023
DBGDGM: Dynamic Brain Graph Deep Generative Model
Graphs are a natural representation of brain activity derived from funct...
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01/23/2023
On the Expressive Power of Geometric Graph Neural Networks
The expressive power of Graph Neural Networks (GNNs) has been studied ex...
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12/07/2022
Learning Graph Search Heuristics
Searching for a path between two nodes in a graph is one of the most wel...
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11/30/2022
A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation
Neural networks with PDEs embedded in their loss functions (physics-info...
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11/29/2022
Continuous Neural Algorithmic Planners
Neural algorithmic reasoning studies the problem of learning algorithms ...
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11/28/2022
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data
Tabular biomedical data is often high-dimensional but with a very small ...
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11/28/2022
Transductive Kernels for Gaussian Processes on Graphs
Kernels on graphs have had limited options for node-level problems. To a...
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11/26/2022
Latent Graph Inference using Product Manifolds
Graph Neural Networks usually rely on the assumption that the graph topo...
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11/20/2022
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery
By one of the most fundamental principles in physics, a dynamical system...
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11/14/2022
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations
Recent work has suggested post-hoc explainers might be ineffective for d...
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11/13/2022
Goal-Conditioned Reinforcement Learning in the Presence of an Adversary
Reinforcement learning has seen increasing applications in real-world co...
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11/13/2022
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
Shadows in videos are difficult to detect because of the large shadow de...
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11/11/2022
Graph-Conditioned MLP for High-Dimensional Tabular Biomedical Data
Genome-wide studies leveraging recent high-throughput sequencing technol...
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11/09/2022
Graph Neural Networks with Adaptive Readouts
An effective aggregation of node features into a graph-level representat...
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10/27/2022
Explaining the Explainers in Graph Neural Networks: a Comparative Study
Following a fast initial breakthrough in graph based learning, Graph Neu...
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10/24/2022
Structure-based Drug Design with Equivariant Diffusion Models
Structure-based drug design (SBDD) aims to design small-molecule ligands...
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10/13/2022
Global Explainability of GNNs via Logic Combination of Learned Concepts
While instance-level explanation of GNN is a well-studied problem with p...
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09/27/2022
DBGSL: Dynamic Brain Graph Structure Learning
Functional connectivity (FC) between regions of the brain is commonly es...
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09/19/2022
Distributed representations of graphs for drug pair scoring
In this paper we study the practicality and usefulness of incorporating ...
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09/19/2022