QLS

Europe/Rome 2022-05-16 08:00:00 2022-05-20 22:00:00 Random Matrices, Random Graphs and Statistical Physics for Machine Learning and Inference | (smr 3703) An ICTP Hybrid Meeting. You can submit your application for participation in presence or online. This school on random matrices and graphs, machine learning and statistical physics will emphasize the strong connections between these fields, strenghten the analytical toolbox of the students and provide a modern vision of the challenges in high-dimensional statistics.   Inference and learning systems have been studied for decades. But the richness of contemporary high-dimensional statistical models (deep neural networks, community detection and inference on graphs, tensor factorization etc) require novel ideas and analytical methods. In particular, blending methods from random matrix theory, statistical physics and information theory is particularly promising. The school aims at providing an overview of recent progresses in this interdisciplinary field by worldwide experts coming from different backgrounds, but who all share a common goal of better modelling complex systems processing large datasets, and understanding their fundamental and algorithmic limitations.      Topics: High-dimensional statistics Random matrix theory Statistical physics Information theory Theoretical machine learning Graph theory Lecturers: C. MALE, Bordeaux University, France L. MASSOULIÉ, INRIA Paris, France M. LELARGE, INRIA Paris & Ecole Polytechnique, France M. POTTERS, Capital Fund Management, France P. VIVO, King's College London, UK Grants: A limited number of grants are available to support the attendance of selected participants. There is no registration fee. In person participation: As regards the COVID-19 policy, we advise to follow the updated rules available on the ICTP page Access Guidelines for Visitors.     ICTP ICTP pio@ictp.it 16 May 2022 - 20 May 2022

Europe/Rome 2022-06-06 08:00:00 2022-06-24 22:00:00 Eco-evolutionary Dynamics of Microbial Communities Across Scales | (smr 3714) An ICTP Meeting in presence Microbial communities populate every corner of our planet, providing essential services to the ecosystems they are part of. The forces shaping their organization act on wide spatial and temporal scales. The fundamental constituents of communities are individual cells, which, typically, experience a local environment of the order of tens of microns and duplicate as fast as 20 minutes. On the other hand, microbial communities modify the environment on a scale of tens of meters. Understanding how the interactions, the environmental fluctuations, and the phenotypic heterogeneity occurring at the micro-scale affect the large-scale properties of microbial communities is one of the main challenges in microbial ecology. More broadly, microbial communities are the prototypical example of complex adaptive systems: a large number of heterogeneous, adaptive, agents interact at a microscopic scale giving rise to emergent properties at the macroscopic scale. This huddle aims at bringing together experimentalists and theorists to develop new understanding and new approaches to connect the fundamental biological processes occurring at the microscale with the phenomena observed at the macroscale.   Topics: Microbial ecology Theoretical community ecology Spatial ecology Eco-evolutionary dynamics Stochastic processes Single-cell experimental ecology Macroecology Ecological networks Population genetics   Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee. In person participation: As regards the COVID-19 policy, we advise to follow the updated rules available on the ICTP page Access Guidelines for Visitors.   ICTP ICTP pio@ictp.it 6 Jun 2022 - 24 Jun 2022

Europe/Rome 2022-06-27 08:00:00 2022-06-30 22:00:00 Youth in High-Dimensions: Recent Progress in Machine Learning, High-Dimensional Statistics and Inference | (smr 3719) An ICTP Hybrid Meeting “Youth in high dimensions” gives to young researchers from academia and industry the opportunity to gather and present recent results on high-dimensional statistical problems, in areas ranging from machine learning and inference to neuroscience or statistical physics.   Typical problems in high-dimensions include estimating noisy signals (compressed sensing, PCA and tensor decomposition), analysing (deep) neural-networks, detecting communities in large networks, or modelling disordered spin systems. These seemingly unrelated problems share many similarities in their phenomenology and in the tools used to analyse them. The core of the field is made of a very active, diverse and quickly expanding community of physicists, computer scientists, mathematicians, information theorists and engineers, with the common desire to tackle increasingly challenging problems at the forefront of data science. This conference aims at reinforcing the links among this interdisciplinary community, and in particular of its youngest theory-oriented members, and to bring forward the latest development happening in the high-dimensional world.   Topics: High-dimensional statistics Statistical physics Machine learning  Complex systems  Random matrix theory Computational neuroscience Speakers: A. ALTIERI, Université Paris Cité, France A. BIETTI, NYU, USA E. CORNACCHIA, EPFL, Switzerland N. FLAMMARION, EPFL, Switzerland L. FOINI, CNRS IPhT Université Paris-Saclay, France M. GEIGER, MIT, USA J. HAN, Flatiron Institute, USA J. KADMON, The Hebrew University, Israel J. KO, ENS Lyon, France M. LINDSEY, NYU, USA B. MCKENNA, IST, Austria C. PEHLEVAN, Harvard University, USA N. RAZIN, Tel Aviv University, Israel D. SCHRÖDER, ETH, Switzerland M. SELLKE, Stanford University, USA G. SICURO, King’s College London, UK C. THRAMPOULIDIS, University of British Columbia, USA Y. WEI, University of Pennsylvania, USA F. YANG, ETH, Switzerland Y. ZHU, University of California, USA   Please note in the application form you will be asked to submit a poster abstract. A number of abstracts will be selected for the poster session. Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee. In person participation: As regards the COVID-19 policy, we advise to follow the updated rules available on the ICTP page Access Guidelines for Visitors.   ICTP ICTP pio@ictp.it 27 Jun 2022 - 30 Jun 2022

Europe/Rome 2022-07-25 08:00:00 2022-07-29 22:00:00 Workshop on Quantitative Human Ecology | (smr 3728) An ICTP Hybrid Meeting. You can submit your application for participation in presence or online. The workshop aims at fostering a science based consensus on challenges that are central to sustainability, such as the rising inequality, demographic crises, migrations, biodiversity loss, and impacts of climate change. A wider integration of methods from hard sciences to statistical approaches and demography is needed in order to pursue the identification of general mechanisms, universal features, and stylized facts that are the roots of an comprehensive understanding of the determinants of sustainability. In particular the workshop will tackle key challenges such as: 1) the mismatch of time-scales between policy measures and the relevant systems' dynamics, 2) accounting for the human impacts and agency and 3) the integration of different dimensions (e.g. inequality, climate, biodiversity, etc). The ultimate aim is to shed light on the determinants of sustainability in systems of human and non-human interacting agents, with a large scale connectivity in order to delineate a research agenda on how basic sciences can contribute to sustainable development. The workshop will bring together scientists from different disciplines (economics, ecology, demography, physics, complex systems science, climatology, epidemiology, social sciences, and intelligent systems) in order to promote a wider integration of methods across disciplines. Speakers include: S. BARRETT, Columbia University, USA M. BENZAQUEN, Ecole Polytechnique, France L. BETTENCOURT, University of Chicago, USA J. COHEN, Rockefeller University and Columbia University, USA S. CRABTREE, Santa Fe Institute, USA M. DACOROGNA, University of Zurich, Switzerland A. DASGUPTA, UK Foreign, Commonwealth and Development Office, Nigeria P. DASGUPTA, Cambridge University, UK S. DIAZ, University of Cordoba, Argentina B. FATH, Towson University, Maryland, USA & IIASA, Austria M. FRANCO GAVONEL, Oxford University, UK M. GALESIC, Santa Fe Institute, USA S. GIETEL-BASTEN, Hong Kong University of Science and Technology, Hong Kong P. GONG, Tsinghua University, China A. GOUJON, IIASA and Austrian Academy of Sciences, Vienna Institute of Demography, Austria M. LOREAU, CNRS, France P.A. MARQUET, Pontificia Universidad Católica de Chile and Santa Fe Institute, USA E. OMODEI, Central European University, Austria S. SCHERBOV, IIASA, Austria D.P. SCHRAG, Harvard University, USA J. SHAWE-TAYLOR, University College London UK and IRCAI Ljubljana, Slovenia A. VESPIGNANI, Northeastern University, USA D. WOLPERT, Santa Fe Institute, USA Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee. In person participation: As regards the COVID-19 policy, we advise to follow the updated rules available on the ICTP page Access Guidelines for Visitors.   ICTP ICTP pio@ictp.it 25 Jul 2022 - 29 Jul 2022