Journal & Conference
Use this page as a quick reference for venues that frequently publish time-series research, forecasting methods, anomaly detection work, and applied machine learning papers.
Quick Start
| Goal | Where to Start |
|---|---|
| Keep up with the newest methods | NeurIPS, ICML, ICLR, KDD |
| Read mature forecasting work | International Journal of Forecasting, Journal of Time Series Analysis |
| Find applied industry papers | Expert Systems with Applications, TKDE, KDD |
| Track anomaly detection and data mining work | KDD, ICDM, SDM, Data Mining and Knowledge Discovery |
| Search broadly by topic | Google Scholar, DBLP, OpenReview, Semantic Scholar |
Journals
| Venue | Focus |
|---|---|
| International Journal of Forecasting | Forecasting methods, evaluation, business forecasting, and practical applications. |
| Forecasting | Open-access venue for forecasting methods and applications. |
| Journal of Time Series Analysis | Statistical time-series theory, methodology, and applications. |
| Technometrics | Statistical methods in engineering, industry, quality, and modeling. |
| Journal of Machine Learning Research | Broad machine learning research, including time-series modeling and evaluation. |
| Data Mining and Knowledge Discovery | Data mining, anomaly detection, sequence mining, and large-scale learning. |
| Machine Learning | Core machine learning methods, theory, and empirical studies. |
| IEEE Transactions on Knowledge and Data Engineering | Data mining, representation learning, temporal modeling, and applied ML systems. |
| Pattern Recognition | Pattern recognition, sequence modeling, and signal-related learning tasks. |
| Expert Systems with Applications | Applied machine learning, forecasting, anomaly detection, and decision-support systems. |
| IEEE Transactions on Neural Networks and Learning Systems | Deep learning, sequence modeling, and modern neural architectures. |
| Information Sciences | Applied AI, data mining, forecasting, optimization, and hybrid models. |
Conferences
| Venue | Focus |
|---|---|
| NeurIPS | Frontier machine learning research, including sequence modeling and foundation models. |
| ICML | Core machine learning conference with frequent time-series and probabilistic modeling papers. |
| ICLR | Representation learning, deep learning, transformers, and modern sequence modeling. |
| KDD | Applied data mining, time-series forecasting, anomaly detection, and industrial ML. |
| IEEE ICDM | Data mining methods and applications, including temporal and streaming data. |
| SDM | Data mining and analytics with regular sequence and forecasting work. |
| AAAI | Broad AI conference with forecasting, anomaly detection, and temporal reasoning papers. |
| IJCAI | General AI research with relevant work in temporal learning and reasoning. |
| AISTATS | Statistical machine learning, probabilistic modeling, and inference for time-dependent data. |
| UAI | Uncertainty, graphical models, causality, and probabilistic sequence modeling. |
| ECML PKDD | European venue for machine learning and data mining with regular temporal-data work. |
| The Web Conference (WWW) | Web-scale learning, user behavior modeling, and applied temporal prediction. |
Calls for Papers
| Resource | Use |
|---|---|
| WikiCFP | Broad CFP aggregator for conferences, workshops, and special issues. |
| Conference Alerts | Large directory of upcoming conferences across research areas. |
| All Conference Alert | Searchable CFP-style portal by topic and country. |
| OpenReview Venue Pages | Useful for active ML/AI venues that manage submissions through OpenReview. |
Search Portals
| Resource | Best For |
|---|---|
| Google Scholar | Broad paper search, citation tracking, and author profiles. |
| Semantic Scholar | Fast discovery, citation graphs, and related-paper exploration. |
| DBLP | Clean conference and journal bibliographic lookup for CS venues. |
| OpenReview | Reading recent ML conference submissions, reviews, and decisions. |
| arXiv | Latest preprints before formal journal or conference publication. |
| Papers with Code | Linking papers with implementations, leaderboards, and datasets. |
Suggested Reading Strategy
- Use journals when you want foundational methods, clearer evaluation, and more complete application discussion.
- Use conferences when you want fast-moving topics such as transformers, foundation models, zero-shot forecasting, and new anomaly-detection benchmarks.
- Start from a survey page, then search the target venue for the last two to three years of papers on the same topic.
- When a paper looks promising, follow citations forward with Google Scholar or Semantic Scholar before committing time to implementation.
How to Use This Page
- Start with journals if you want mature, polished work and application-heavy studies.
- Start with conferences if you want the fastest view of new methods and current research trends.
- For recent model families, pair this page with SOTA Survey Papers and LLM for Time Series.