International Conference on Machine Learning and Physical Science

Conference Date

2022-08-26 - 2022-08-28

Place

Qingdao, China

Submission Deadline

2022-07-20

E-mail

icmlps@icmlps.net

Telephone

+86-15634396373

Description

2022 International Conference on Machine Learning and Physical Science (ICMLPS-22, Physical and Virtual Mode)
On August 26-28, 2022
In Qingdao University International Hotel, Qingdao, China


ICMLPS is supported by Qingdao University, Shenyang University of Technology, and Engineering Technology Development and Innovation Society (ETDIS), etc. Machine learning methods have had great success in learning complex representations of data that enable novel modeling and data processing approaches in many scientific disciplines. Physical sciences span problems and challenges at all scales in the universe: from finding exoplanets in trillions of sky pixels, to developing solutions to the quantum many-body problem and combinatorial problems, to detecting anomalies in event streams from the Large Hadron Collider, to predicting how extreme weather events will vary with climate change. Tackling a number of associated data-intensive tasks including, but not limited to, segmentation, computer vision, sequence modeling, causal reasoning, generative modeling, and probabilistic inference are critical for furthering scientific discovery in these and many other areas. In addition to using machine learning models for scientific discovery, the ability to interpret what a model has learned is receiving an increasing amount of attention.
ICMLPS aims to bring together computer scientists, mathematicians and physical scientists who are interested in applying machine learning to various outstanding physical problems including in inverse problems, approximating physical processes, understanding what a learned model represents, and connecting tools and insights from the physical sciences to the study of machine learning models. In particular, it invites researchers to contribute full papers and abstracts that demonstrate cutting-edge progress in the application of machine learning techniques to real-world problems in the physical sciences and/or using physical insights to understand and improve machine learning techniques.
By bringing together machine learning researchers and physical scientists who apply machine learning, we expect to strengthen the interdisciplinary dialogue, introduce exciting new open problems to the broader community, and stimulate the production of new approaches to solving challenging open problems in the sciences. Invited talks from leading individuals in both communities will cover the state-of-the-art techniques and set the stage for this conference.
We cordially invite you to submit original, high-quality manuscripts. Accepted and presented papers will be published in conference proceedings, which will be indexed by SCOPUS, Ei Compendex (CPX), Google Scholar, etc.

==Call for paper==

Application of machine learning to physical sciences
Generative models
Likelihood-free inference
Variational inference
Simulation-based inference
Implicit models
Probabilistic models
Model interpretability
Approximate bayesian computation
Strategies for incorporating prior scientific knowledge into machine learning algorithms
Experimental design
Any other area related to the subject of the ICMLPS
Image Indexing and Retrieval For more topics: 
https://icmlps.net/CFP/

==Submission==

Prospective authors are invited to submit full-length papers (4-5 pages for technical content, including figures and possible references) or abstracts (for oral presentations without publication) via the Hcconf management system. Accepted papers and abstracts will be scheduled in lecture and poster sessions. All submissions will be sent to at least two reviewers for reviewing, and it will take about 15 working days.
Hcconf management system: 
https://www.hcconf.tech/submission/icmlps -22

==Publication==

Submissions will be reviewed by the conference technical committees based on originality, relevance to conference, structure and readability. Accepted and presented papers will be published in conference proceedings, which will be submitted to SCOPUS, Ei Compendex (CPX), Google Scholar, etc for indexing.

==Program and schedule==

Participants should arrange your time properly according to the conference schedule. The brief version is simply for reference. The detailed version may have slight differences, which will be released about 30 days before the conference. The provisional program is as follows: https://icmlps.net/Program/

==Contact us==

Conference Secretary: Mr. Juliano Lee
Email: icmlps@icmlps.net
Wechat No.: conf2icml
Tel: +86-15634396373
(Office time 9:30 - 18:00, Time zone: GMT+8; Monday to Friday)