Seminars on Machine Learning in  Quantum Chemistry and Quantum Computing for Quantum Chemistry (SMLQC)

Seminars on Machine Learning in Quantum Chemistry and Quantum Computing for Quantum Chemistry (SMLQC) are flexible online lectures and tutorials for highlighting recent developments and providing hands-on experience on the title topics as well as networking opportunities. SMLQC sessions are organized to bridge Symposia on Machine Learning and Quantum Chemistry, the first one held in 2021 in Xiamen, China (online) and the second one to be held in 2023 in Uppsala, Sweden (hybrid). The real-time interaction is enabled via a dedicated Slack workspace which already has many researchers active in the title fields.

Format

Format is flexible with roughly biweekly sessions online usually divided into two sections:

– Scientific section

focused on recent developments which can be, e.g., highlighting recently published papers.

Talks are limited to 20 min so that people can attend them during their “coffee break”. The question part will be up to 5 min if scientific section is followed by a tutorial session where the speaker can elaborate more on the questions. Otherwise, if no tutorial session is given, then question part will be open until the speaker or participants give up.

– Tutorial/hands-on section

Dedicated to providing instructions on program use and practical understanding of the underlying ML theory. The materials used in the talks (e.g., Jupyter notebooks, Python scripts, etc.) could be made available for the participants via GitHub, Google Colab, etc. or the SMLQC website under the allowance of the speaker. No strict time limitations but we recommend up to 1 hour.

We particularly encourage and give platform to young researchers (e.g., postdocs, PhDs, etc.) to give seminars.

All our sessions will also have break out rooms in Zoom where participants can have further exchange or fix some specific problems during hands-on session.

If speakers agree, the seminars will be recorded and uploaded on SMLQC YouTube channel.

Speakers

Speakers are invited by the organizing committee and can be selected according to the suggestions of SMLQC participants, e.g., via voting in our Slack workspace. Self-nominations are also encouraged!

Organizers

Current organizers in alphabetic order:

Soon, organizers will be joined by more specialists with diverse expertise.

Speakers

Upcoming seminars

How to join

Join Zoom Meeting

https://zoom.us/j/86004422973?pwd=WjNKQlEydmdFL3hJbUx4NjByYjVJZz09

Meeting ID: 860 0442 2973

Passcode: 703098

Past seminars

Lecture on Machine Learning-based Quantum Dissipative Dynamics
The tutorial for Machine Learning-based Quantum Dissipative Dynamics
Max Pinheiro Jr | Nonadiabatic Molecular Dynamics with Machine Learning | Lecture
Max Pinheiro Jr | Unsupervised Learning Analysis of Molecular Dynamics (ULaMDyn) program | Tutorial
Pascal Friederich| ML for Simulation, Understanding, and Design of Molecules and Materials| Lecture
Pascal Friederich| ML for Simulation, Understanding, and Design of Molecules and Materials| Tutorial
Daniel Schwalbe-Koda | Adversarial Sampling and Extrapolation Trends in NN Potentials | Lecture
Daniel Schwalbe-Koda | Adversarial Sampling and Extrapolation Trends in NN Potentials | Tutorial