Dynamic Link Prediction

Benchmarks archive 2025-07-28

10 leaderboard tables shown for this task, 10 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

8 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

20 shown of 20 papers with code (41 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
  26 Feb 2019 10 repositories listed Syntology ran 3 of 11 samples · 8 unverified · 1 pointer-only (licence)
  Existing approaches typically resort to node embeddings and use a recurrent neural network (RNN, broadly speaking) to regulate the embeddings and learn the temporal dynamics.
• Canonical Tensor Decomposition for Knowledge Base Completion
  19 Jun 2018 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  The problem of Knowledge Base Completion can be framed as a 3rd-order binary tensor completion problem.
• Towards Better Dynamic Graph Learning: New Architecture and Unified Library
  23 Mar 2023 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  We propose DyGFormer, a new Transformer-based architecture for dynamic graph learning.
• DyG2Vec: Efficient Representation Learning for Dynamic Graphs
  30 Oct 2022 2 repositories listed
  Temporal graph neural networks have shown promising results in learning inductive representations by automatically extracting temporal patterns.
• Variational Graph Recurrent Neural Networks
  26 Aug 2019 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Representation learning over graph structured data has been mostly studied in static graph settings while efforts for modeling dynamic graphs are still scant.
• DyRep: Learning Representations over Dynamic Graphs
  1 May 2019 2 repositories listed
  We present DyRep - a novel modeling framework for dynamic graphs that posits representation learning as a latent mediation process bridging two observed processes namely -- dynamics of the network (realized as…
• Supra-Laplacian Encoding for Transformer on Dynamic Graphs
  26 Sep 2024 1 repository listed Syntology ran 6 of 6 samples · 0 unverified
  Fully connected Graph Transformers (GT) have rapidly become prominent in the static graph community as an alternative to Message-Passing models, which suffer from a lack of expressivity, oversquashing, and…
• Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks
  22 Aug 2024 1 repository listed
  In this study, we introduce a self-supervised method for learning representations of temporal networks and employ these representations in the dynamic link prediction task.
• Temporal receptive field in dynamic graph learning: A comprehensive analysis
  17 Jul 2024 1 repository listed
  Dynamic link prediction is a critical task in the analysis of evolving networks, with applications ranging from recommender systems to economic exchanges.
• Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms
  27 May 2024 1 repository listed
  However, a single metric is not sufficient to fully capture the differences between DLP algorithms, and is prone to overly optimistic performance evaluation.
• New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs
  30 Nov 2023 1 repository listed
  We leverage these visualization tools to investigate the effect of negative sampling on the predictive performance, at the node and edge level.
• Exploring Time Granularity on Temporal Graphs for Dynamic Link Prediction in Real-world Networks
  21 Nov 2023 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 3 pointer-only (licence)
  Dynamic Graph Neural Networks (DGNNs) have emerged as the predominant approach for processing dynamic graph-structured data.
• EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning
  22 Mar 2023 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics directly in continuous time domain for its flexibility.
• DyCSC: Modeling the Evolutionary Process of Dynamic Networks Based on Cluster Structure
  23 Oct 2022 1 repository listed
  Temporal networks are an important type of network whose topological structure changes over time.
• Towards Better Evaluation for Dynamic Link Prediction
  20 Jul 2022 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  To evaluate against more difficult negative edges, we introduce two more challenging negative sampling strategies that improve robustness and better match real-world applications.
• Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction
  24 Apr 2022 1 repository listed
  In this paper, we propose a formalized approach to this problem with a framework we call EULER.
• Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
  30 Mar 2022 1 repository listed Syntology ran 0 of 2 samples · 2 unverified · 1 pointer-only (licence)
  User interests are usually dynamic in the real world, which poses both theoretical and practical challenges for learning accurate preferences from rich behavior data.
• Benchmarking Graph Neural Networks on Dynamic Link Prediction
  29 Sep 2021 1 repository listed
  We compare link prediction heuristics, GNNs, discrete DGNNs, and continuous DGNNs on dynamic link prediction.
• Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions
  23 Sep 2019 1 repository listed
  We consider a common case in which edges can be short term interactions (e.
• dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning
  7 Sep 2018 1 repository listed
  Capturing such evolution is key to predicting the properties of unseen networks.

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.