Cover Image

Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nouranizadeh, Amirhossein, Far, Fatemeh Tabatabaei, Rahmati, Mohammad
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Neural and Evolutionary Computing I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Scaling Deep Neural Networks with Predictive Coding: Theory and Practice
by: Innocenti, Francesco
Published: (2025)

IP$^{2}$-RSNN: Bi-level Intrinsic Plasticity Enables Learning-to-learn in Recurrent Spiking Neural Networks
by: Yu, Yingchao, et al.
Published: (2025)

Introducing Echo Networks for Computational Neuroevolution
by: Kroos, Christian, et al.
Published: (2026)

Evolving Deep Learning Optimizers
by: Marfinetz, Mitchell
Published: (2025)

Extending Spike-Timing Dependent Plasticity to Learning Synaptic Delays
by: Dominijanni, Marissa, et al.
Published: (2025)

Multi-objective Binary Coordinate Search for Feature Selection
by: Miyandoab, Sevil Zanjani, et al.
Published: (2024)

Evaluating Brain-Inspired Modular Training in Automated Circuit Discovery for Mechanistic Interpretability
by: Nainani, Jatin
Published: (2024)

Compact NSGA-II for Multi-objective Feature Selection
by: Miyandoab, Sevil Zanjani, et al.
Published: (2024)

Batchless Normalization: How to Normalize Activations Across Instances with Minimal Memory Requirements
by: Berger, Benjamin, et al.
Published: (2022)

Increasing biases can be more efficient than increasing weights
by: Metta, Carlo, et al.
Published: (2023)

GAAPO: Genetic Algorithmic Applied to Prompt Optimization
by: Sécheresse, Xavier, et al.
Published: (2025)

On the Infinite Width and Depth Limits of Predictive Coding Networks
by: Innocenti, Francesco, et al.
Published: (2026)

Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?
by: Innocenti, Francesco, et al.
Published: (2024)

$μ$PC: Scaling Predictive Coding to 100+ Layer Networks
by: Innocenti, Francesco, et al.
Published: (2025)

Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
by: Lee, Justin, et al.
Published: (2025)

Reward-Modulated Local Learning in Spiking Encoders: Controlled Benchmarks with STDP and Hybrid Rate Readouts
by: Chakraborty, Debjyoti
Published: (2026)

Shrinkage Initialization for Smooth Learning of Neural Networks
by: Cheng, Miao, et al.
Published: (2025)

Theoretical Analysis of the Advantage of Deepening Neural Networks
by: Esaki, Yasushi, et al.
Published: (2020)

Controlling Recurrent Neural Networks by Conceptors
by: Jaeger, Herbert
Published: (2014)

Game-Theoretic Gradient Control for Robust Neural Network Training
by: Zaitseva, Maria, et al.
Published: (2025)

Collapse or Preserve: Data-Dependent Temporal Aggregation for Spiking Neural Network Acceleration
by: Qin, Jiahao
Published: (2026)

K-Way Energy Probes for Metacognition Reduce to Softmax in Discriminative Predictive Coding Networks
by: Cacioli, Jon-Paul
Published: (2026)

Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation
by: Weber, Leander, et al.
Published: (2023)

A Technical Note on the Architectural Effects on Maximum Dependency Lengths of Recurrent Neural Networks
by: Kent, Jonathan S., et al.
Published: (2024)

Combining Trained Models in Reinforcement Learning
by: Patil, Ujjwal, et al.
Published: (2026)

Efficient NAS with FaDE on Hierarchical Spaces
by: Neumeyer, Simon, et al.
Published: (2024)

Rapid training of Hamiltonian graph networks using random features
by: Rahma, Atamert, et al.
Published: (2025)

Solar Irradiation Forecasting using Genetic Algorithms
by: Gunasekaran, V., et al.
Published: (2021)

Alternating Gradient Flow Utility: A Unified Metric for Structural Pruning and Dynamic Routing in Deep Networks
by: Qian, Tianhao, et al.
Published: (2026)

A Linear Programming Enhanced Genetic Algorithm for Hyperparameter Tuning in Machine Learning
by: Sinha, Ankur, et al.
Published: (2024)

Full Domain Analysis in Fluid Dynamics
by: Hagg, Alexander, et al.
Published: (2025)

FF-INT8: Efficient Forward-Forward DNN Training on Edge Devices with INT8 Precision
by: Ma, Jingxiao, et al.
Published: (2025)

Dynamical Alignment: A Principle for Adaptive Neural Computation
by: Chen, Xia
Published: (2025)

Shapley Value-Guided Adaptive Ensemble Learning for Explainable Financial Fraud Detection with U.S. Regulatory Compliance Validation
by: Uddin, Mohammad Nasir, et al.
Published: (2026)

Enhanced Protein Intrinsic Disorder Prediction Through Dual-View Multiscale Features and Multi-objective Evolutionary Algorithm
by: Wang, Shaokuan, et al.
Published: (2026)

Self-Distillation Learning Based on Temporal-Spatial Consistency for Spiking Neural Networks
by: Zuo, Lin, et al.
Published: (2024)

Pre-train to Gain: Robust Learning Without Clean Labels
by: Szczecina, David, et al.
Published: (2025)

Searching Search Spaces: Meta-evolving a Geometric Encoding for Neural Networks
by: Kunze, Tarek, et al.
Published: (2024)

Breaching the Bottleneck: Evolutionary Transition from Reward-Driven Learning to Reward-Agnostic Domain-Adapted Learning in Neuromodulated Neural Nets
by: Arnold, Solvi, et al.
Published: (2024)

Pulling Back the Curtain on Deep Networks
by: Satkiewicz, Maciej, et al.
Published: (2025)