This journal is not listed in the SCIE, SSCI, AHCI, ESCI, Scopus or JCR 2024 lists. That does not make it unreliable, but check its indexing, peer review and fees carefully.
How to spot predatory journals →01Indexing
Indexing of Transactions on Machine Learning Research
| List | Status |
|---|---|
| Science Citation Index Expanded (SCIE) | Not listed |
| Social Sciences Citation Index (SSCI) | Not listed |
| Arts & Humanities Citation Index (AHCI) | Not listed |
| Emerging Sources Citation Index (ESCI) | Not listed |
| Scopus | Not listed |
| Journal Citation Reports 2024 | Not listed |
From the indexing lists used on ScholarsColab, updated 1 March 2026. Indexing can change: confirm on the Web of Science Master Journal List or the Scopus source list before submitting. Official Journal Impact Factors and JCR quartiles are published by Clarivate; the impact factor and quartile on this page are calculated from OpenAlex open data (see how the impact factor works).
02What it publishes
What Transactions on Machine Learning Research publishes: real papers
Words that appear most often in the titles of the papers published here that we track. Choose one to see those papers:
03Published papers
Papers published in Transactions on Machine Learning Research
Papers from the publication records ScholarsColab tracks, with their year and citations. Author names are not shown.
- Neighborhood gradient mean: An efficient decentralized learning method for non-iid data202310 citations
- Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning20260 citations
- Graph Coarsening using Game Theoretic Approach20260 citations
- Still Competitive: Revisiting Recurrent Models for Irregular Time Series Prediction20260 citations
- Domain-oriented time series inference agents for reasoning and automated analysis20260 citations
- A survey on federated fine-tuning of large language models20260 citations
- Unifying VXAI: a systematic review and framework for the evaluation of explainable AI20260 citations
- From Link Prediction to Forecasting: Addressing Challenges in Batch-based Temporal Graph Learning20260 citations
- Beyond Affinity: A Benchmark of 1D, 2D, and 3D Methods Reveals Critical Trade-offs in Structure-Based Drug Design20260 citations
- Empowering Power Outage Prediction with Spatially Aware Hybrid Graph Neural Networks and Contrastive Learning20260 citations
- LJ-Bench: Ontology-Based Benchmark for US Crime20260 citations
- GraphMERT: Efficient and Scalable Distillation of Reliable Knowledge Graphs from Unstructured Data20260 citations
- Deep multimodal learning with missing modality: A survey20260 citations
- Reliable and Responsible Foundation Models: A Comprehensive Survey20260 citations
- Reduced-order neural operators: Learning lagrangian dynamics on highly sparse graphs20260 citations
- HypCBC: Domain-Invariant Hyperbolic Cross-Branch Consistency for Generalizable Medical Image Analysis20260 citations
- Prompt-based adaptation in large-scale vision models: A survey20260 citations
- Vicon: Vision in-context operator networks for multi-physics fluid dynamics prediction20260 citations
- Diversity boosts AI-generated text detection20260 citations
- Genomic Next-Token Predictors are In-Context Learners20260 citations
- Wikipedia in the era of llms: Evolution and risks20260 citations
- Link prediction with relational hypergraphs20250 citations
- Combining machine learning defenses without conflicts20250 citations
- Convergence properties of natural gradient descent for minimizing KL divergence20250 citations
- A survey of state representation learning for deep reinforcement learning20250 citations
- Over-parameterised shallow neural networks with asymmetrical node scaling: Global convergence guarantees and feature learning20250 citations
- Revisiting data augmentation for ultrasound images20250 citations
- On the challenges and opportunities in generative ai20250 citations
- Open problems in technical ai governance20250 citations
- Cluster and predict latent patches for improved masked image modeling20250 citations
- Estimating the Event-Related Potential from Few EEG Trials20250 citations
- Enhancing Physics-Informed Neural Networks Through Feature Engineering20250 citations
- Cross-Domain Graph Anomaly Detection via Test-Time Training with Homophily-Guided Self-Supervision20250 citations
- On the Hardness of Computing Counterfactual and Semifactual Explanations in XAI20250 citations
- Conditional image synthesis with diffusion models: A survey20250 citations
- Explaining bayesian neural networks20250 citations
- STLDM: Spatio-Temporal Latent Diffusion Model for Precipitation Nowcasting20250 citations
- Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics20250 citations
- A baseline method for removing invisible image watermarks using deep image prior20250 citations
- Actalign: Zero-shot fine-grained video classification via language-guided sequence alignment20250 citations
- Privacy risks and preservation methods in explainable artificial intelligence: a scoping review20250 citations
- Generalized out-of-distribution detection and beyond in vision language model era: A survey20250 citations
- Llm-select: Feature selection with large language models20250 citations
- M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations20250 citations
- Beyond Instance Consistency: Investigating View Diversity in Self-supervised Learning20250 citations
- Beyond Marginals: Learning Joint Spatio-Temporal Patterns for Multivariate Anomaly Detection20250 citations
- Adaptive physics-informed neural networks: A survey20250 citations
- Preserving privacy in large language models: A survey on current threats and solutions20250 citations
- Continual Pre-training of MoEs: How robust is your router?20250 citations
- Symmetry in neural network parameter spaces20250 citations
- A distance-based anomaly detection framework for deep reinforcement learning20240 citations
- Towards backwards-compatible data with confounded domain adaptation20240 citations
- Attending to graph transformers20240 citations
- Interpreting global perturbation robustness of image models using axiomatic spectral importance decomposition20240 citations
- Learning-based link anomaly detection in continuous-time dynamic graphs20240 citations
- AdaWaveNet: Adaptive wavelet network for time series analysis20240 citations
- A survey on large language models for critical societal domains: Finance, healthcare, and law20240 citations
- Path development network with finite-dimensional Lie group representation20240 citations
- Deep-Graph-Sprints: Accelerated Representation Learning in Continuous-Time Dynamic Graphs20240 citations
- Time series continuous modeling for imputation and forecasting with implicit neural representations20240 citations
- Deep neural networks and brain alignment: Brain encoding and decoding (survey)20240 citations
- A Dual-Perspective Approach to Evaluating Feature Attribution Methods20240 citations
- Neural monge map estimation and its applications20230 citations
- Data models for dataset drift controls in machine learning with optical images20230 citations
- Lightweight learner for shared knowledge lifelong learning20230 citations
- On the efficacy of differentially private few-shot image classification20230 citations
- Graph-based multi-ODE neural networks for spatio-temporal traffic forecasting20230 citations
- Foiling explanations in deep neural networks20230 citations
- You only transfer what you share: Intersection-induced graph transfer learning for link prediction20230 citations
- Personalized federated learning: A unified framework and universal optimization techniques20230 citations
- Multi-label node classification on graph-structured data20230 citations
- Graph neural networks designed for different graph types: A survey20230 citations
- Modular deep learning20230 citations
- Extended agriculture-vision: An extension of a large aerial image dataset for agricultural pattern analysis20230 citations
- DyG2Vec: Efficient representation learning for dynamic graphs20230 citations
- Deep learning for bayesian optimization of scientific problems with high-dimensional structure20220 citations
- TLDR: Twin learning for dimensionality reduction20220 citations
- A snapshot of the frontiers of client selection in federated learning20220 citations
04Reviewer comments
Reviewer comments and rejection reasons for Transactions on Machine Learning Research
No reviewer or editor comments have been shared for this journal yet. Did you submit here? Help other researchers by sharing the comments you received, anonymously.
Share reviewer comments for this journal →Across the reviewer comments researchers have shared with us, the points raised most often are figures, tables and equations (21%), literature and references (12%) and novelty and contribution (10%). Before you submit to Transactions on Machine Learning Research, a Manuscript Audit by a PhD reviewer in your area checks your paper against exactly these points.
Audit my paper before I submit →Not sure yet? Check if your paper is ready for this journal: free, no AI, under 5 secondsPreparing to submit here? Make sure reviewers don't stop at the issues they raise most often. A PhD reviewer in your area can audit your manuscript section by section, and we can convert it into the journal's LaTeX template.
05Similar journals
Journals similar to Transactions on Machine Learning Research
Journals that publish the closest work to the papers above:
- Journal of Combinatorial Mathematics and Combinatorial ComputingScopus6 similar papers
- International Journal for Housing Science and Its ApplicationsScopus5 similar papers
- Journal of Theoretical and Applied Information TechnologyScopus3 similar papers
- SustainabilitySCIESSCIScopusJCR 20244 similar papers
- JOURNAL OF LATEX CLASS FILESNot listed in our indexing lists7 similar papers
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06Journal Finder
Find the right journal for your paper
Is Transactions on Machine Learning Research right for your paper? Compare journals
Paste your title, keywords or abstract. We match it against 156,435 published journal papers, by ScholarsColab mentors and other researchers, and show where the closest work appeared, with each journal’s indexing (SCIE, SSCI, AHCI, ESCI, Scopus, JCR 2024).
How it works: no AI or language model is used. Your words are matched against the titles of real published journal papers, by our mentors and by other researchers (shown without names); journals are ranked by how many closely matching papers they published. Indexing comes from the SCIE, SSCI, AHCI, ESCI, Scopus and JCR 2024 lists, matched by journal name; “not found in our indexing lists” does not prove a journal is unindexed. Always check a journal’s scope and current indexing before submitting.
07Questions
Frequently asked questions
Is Transactions on Machine Learning Research indexed in Scopus?
Transactions on Machine Learning Research is not listed in the Scopus list, according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
Is Transactions on Machine Learning Research an SCIE journal?
Transactions on Machine Learning Research is not listed in SCIE or the other Web of Science indexes, according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
Is Transactions on Machine Learning Research in Journal Citation Reports (JCR)?
Transactions on Machine Learning Research is not listed in the JCR 2024 list, according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
What topics does Transactions on Machine Learning Research publish?
The papers published in Transactions on Machine Learning Research that we track most often mention learning, model, graph, neural, network, survey. Check the journal’s aims and scope for its full coverage.
How many papers published in Transactions on Machine Learning Research does ScholarsColab track?
We track 78 papers published in Transactions on Machine Learning Research between 2022 and 2026, cited 10 times in total, with a median of 0 citations per paper.
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