Meetings/Workshops on Neural Networks and Artificial Intelligence, Machine Learning in the United States (USA)

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1
Machine Learning for Physics and the Physics of Learning
04 Sep 2019 - 08 Dec 2019 • Institute for Pure and Applied Mathematics (IPAM),, United States
Abstract:
Machine Learning (ML) is quickly providing new powerful tools for physicists and other natural scientists to extract essential information from large amounts of data, either from experiments or simulations. This IPAM long program will foster nontrivial research and provoke scientific discussion at the interface between ML and Physics. We aim to go beyond simple fitting of physical models from data and move the discussion to (i) using generative ML methods and active learning in order to generate and design complex and novel physical structures and objects, (ii) obtain models that are physically understable, e.g. by maintaining relations of the predictions to the microscopic physical quantities used as an input, (iii) using ML to learn the physical principles and mathematical structures underlying the data, and (iv) developing new ML methods inspired by methods and models developed in Physics.
Event listing ID:
1065619
2
Workshop II — Interpretable Learning in Physical Sciences
14 Oct 2019 - 18 Oct 2019 • Los Angeles, CA, United States
Abstract:
Part of the Long Program Machine Learning for Physics and the Physics of Learning.

The workshop will include methods to summarize and interpret a complicated learned model (e.g. deep neural network) by interrogating this model about what and why it has learned (e.g. relevance propagation and sensitivity analysis).

Event listing ID:
1170966
3
ADT 2019 — 6th International Conference on Algorithmic Decision Theory
25 Oct 2019 - 27 Oct 2027 • Durham, NC, United States
Abstract:
The ADT 2019 conference focus is on algorithmic decision theory broadly defined, seeking to bring together researchers and practitioners coming from diverse areas of Computer Science, Economics and Operations Research in order to improve the theory and practice of modern decision support.
Topics:
Algorithms, Argumentation Theory, Artificial Intelligence, Computational Social Choice, Database Systems, Decision Analysis, Discrete Mathematics, Game Theory, Machine Learning, Matching, Multi-agent Systems, Multiple Criteria Decision Aiding, Networks, Optimization, Risk Management, and Utility Theory
Event listing ID:
1193871
4
Workshop III: Validation and Guarantees in Learning Physical Models: from Patterns to Governing Equations to Laws of Nature
28 Oct 2019 - 01 Nov 2019 • UCLA, Los Angeles, California, United States
Organizer:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Abstract:
Part of the Long Program Machine Learning for Physics and the Physics of Learning.

This workshop will showcase how to employ mathematical aspects of statistical / information theoretic approaches in ML for the discovery of physical laws from data. Offering statistical guarantees along with the learned models is critical in physics and in areas such as aeronautics, climate science, chemistry, biology, and robotics. We will consider model selection, robust statistics, model-free and adaptive learning, and model validation in the context of both static and dynamic models, such as equations of motion.

Event listing ID:
1170968
5
ICTAI 2019 — 31st International Conference on Tools with Artificial Intelligence
04 Nov 2019 - 06 Nov 2019 • Portland, Oregon, United States
Abstract:
ICTAI 2019: The IEEE International Conference on Tools with Artificial Intelligence (ICTAI) is a leading Conference of AI in the Computer Society providing a major international forum where the creation and exchange of ideas related to artificial intelligence are fostered among academia, industry, and government agencies.
Event listing ID:
1226509
Event website:
6
Workshop IV: Using Physical Insights for Machine Learning
18 Nov 2019 - 22 Nov 2019 • Los Angeles, CA, United States
Organizer:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Abstract:
Part of the Long Program Machine Learning for Physics and the Physics of Learning.

In this workshop we will explore how to use physical intuition and ideas to design new classes of machine learning (ML) algorithms. Physics-inspired sampling algorithms could be used to train ML structures or sample the hyper-parameter space (e.g. deep Neural Networks). Additionally, physics-based models such as Ising/Potts models or energy-based models have influenced ML inference frameworks such as Markov Random Fields and Restricted Boltzmann Machines, and we want to continue the discussion to facilitate this innovation transfer. Finally, physical insight could be used to enhance learning in the situation of scarce data by enforcing smoothness, differentiability or other physical properties relevant to a given problem.

Event listing ID:
1170873
7
ICMLA 2019 — 18th International Conference on Machine Learning and Applications
16 Dec 2019 - 19 Dec 2019 • Boca Raton, FL, United States
Abstract:
The conference provides a leading international forum for the dissemination of original research in ML, with emphasis on applications as well as novel algorithms and systems. Following the success of previous ICMLA conferences, the conference aims to attract researchers and application developers from a wide range of ML related areas, and the recent emergence of Big Data processing brings an urgent need for machine learning to address these new challenges. The conference will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, are especially encouraged.
Event listing ID:
1226484
8
100th AMS Annual Meeting — 19th Conference on Artificial Intelligence for Environmental Science
12 Jan 2020 - 16 Jan 2020 • Boston, MA, United States
9
AI NEXTCon
23 Jan 2020 - 26 Jan 2020 • Seattle, WA, United States
Event listing ID:
1246663
10
Workshop — Deep Learning and Medical Applications
27 Jan 2020 - 31 Jan 2020 • Los Angeles, CA, United States
Organizer:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Abstract:
Rapid advances in deep learning techniques are starting to revolutionize medical imaging. Radiology, disease detection, and tissue imaging are all expected to be facilitated by automated image analysis programs in the near future. Many new interdisciplinary research questions arise; finding solutions with practical significance requires input from mathematicians, bio-physicists, and computational engineers. This workshop aims to bring together researchers from different backgrounds to explore this new frontier of science.
Event listing ID:
1172911
11
Rework Applied AI Summit
30 Jan 2020 - 31 Jan 2020 • San Francisco, CA, United States
12
Rework Deep Learning Summit
30 Jan 2020 - 31 Jan 2020 • San Francisco, CA, United States
13
Rework AI Assistant Summit
30 Jan 2020 - 31 Jan 2020 • San Francisco, CA, United States
Abstract:
Applying ML & deep learning to create AI Assistants & conversational interfaces to create deeper, more personalised one-to-one customer experiences.
Event listing ID:
1246737
14
AAAI 2020 — AAAI Conference on Artificial Intelligence
07 Feb 2020 - 12 Feb 2020 • New York, United States
Event listing ID:
1242445
15
ALT — Algorithmic Learning Theory
08 Feb 2020 - 11 Feb 2020 • San Diego, United States
Event listing ID:
1250303
16
Computational Psychiatry
18 Feb 2020 - 21 Feb 2020 • Los Angeles, CA, United States
Organizer:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Abstract:
Psychiatric disorders are typically diagnosed and evaluated using subjective psychological exams that assess symptoms, thoughts, feelings and behavioral patterns. Ongoing and recent advances in measurements provide EEG, functional MRI, optogenetic, genomic, and metabolic data. Along with mathematical methods developed to analyze these data, a more physiological and quantitative approach for diagnosis and treatment can be envisioned. This workshop will explore how modern computational tools and mathematical modeling can be integrated with measurements to improve psychiatric diagnosis and treatment.
Event listing ID:
1172975
17
O'Reilly AI Conference
27 Apr 2020 - 30 Apr 2020 • New York, NY, United States
Abstract:
Organizations that successfully apply AI tools and strategies compete more effectively. Make plans to join us at the O'Reilly AI Conference and chart your business transformation.
Event listing ID:
1246797
18
AVWS1 — Workshop: Individual Vehicle Autonomy: Perception and Control
05 Oct 2020 - 09 Oct 2020 • Los Angeles, California, United States
Organizer:
IPAM
Abstract:
This workshop will bring together researchers working on the theoretical sides of deep learning techniques for perception and control of automated vehicles with researchers interested in assuring these autonomous systems operate with safety guarantees. Moreover, experts in sensing and imaging technology will be brought to the table, to cover the full pipeline from the collection of the data, over the AI theory and development, all the way to the software and actuation challenges. Additional themes addressed in this workshop include interactions between vehicle sensing and the infrastructure, and cybersecurity aspects related to sensing and machine learning (how to purposefully mislead sensors and AI).
Topics:
Part of the Long Program Mathematical Challenges and Opportunities for Autonomous Vehicles
Event listing ID:
1275162
19
Searches and Machine Learning Meet the Precision Frontier
12 Apr 2021 - 15 Apr 2021 • UC Santa Barbara, United States
Organizer:
Kavli Institute for Theoretical Physics (KITP)
Abstract:
The Large Hadron Collider (LHC) is the world’s facility for probing fundamental physics at the electroweak scale and well beyond. As it enters a new phase of extended data accumulation, two broad challenges emerge: how to fulfill the potential for percent-level precision with the large dataset, and how to maximise the information that can be extracted from each event about the underlying scattering process, in particular with machine learning. Solving these problems will have an impact across a wide range of physics topics: establishing the properties of the newly discovered interactions of the Higgs sector and understanding electroweak symmetry breaking, enhancing the sensitivity of searches for physics beyond the Standard Model (BSM), and precision measurements of a range of fundamental parameters in the Standard Model.
Event listing ID:
1246699


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Last updated: 24 September 2019