Händelser: Matematiska vetenskaperhttp://www.chalmers.se/sv/om-chalmers/kalendariumAktuella händelser på Chalmers tekniska högskolaMon, 05 Dec 2022 11:48:13 +0100http://www.chalmers.se/sv/om-chalmers/kalendariumhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete221206.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete221206.aspxPresentation av mastersarbete<p>MV:L14 och Zoom</p><p>​​Sævar Óli Valdimarsson: Prediction of mass transport properties in 3D microstructures using 2D CNNs</p>https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/KASS-seminar221206.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/KASS-seminar221206.aspxKASS seminar<p>MV:L15, Chalmers tvärgata 3</p><p>​Ming​chen Xia: Intersection theory on Riemann—Zariski spaces and Chern—Weil formulae</p>​​<br />Abstract: Given a holomorphic Hermitian vector bundle (E,h) on a smooth complex variety X, the classical Chern—Weil formula says that the Chern forms of (E,h) represent the Chern classes of E. When h has singularities, the corresponding result fails. When h is positively curved, there are many different ways to make sense of the Chern forms/currents of (E,h). For our problem, the most natural one is the non-pluripolar theory. I will explain the Chern—Weil formulae of the following form: the non-pluripolar Chern currents of singular Hermitian vector bundles represent some algebraic intersection numbers. As we will see, this can not be done using the intersection theory on X. Instead, we need to develop an appropriate intersection theory on the Riemann—Zariski space and interpret the algebraic intersection theory properly. https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Analysis-and-Probability221206.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Analysis-and-Probability221206.aspxAnalysis and Probability Seminar<p>MV:L14 and zoom</p><p>CANCELLED</p>​​<br />​https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/TLM-seminarium221207.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/TLM-seminarium221207.aspxTLM-seminarium<p>MV:L15 och Zoom</p><p>​​Samverkansseminarium: Idéutbyte och samverkan mellan grupperna på Matematik och Fysik</p>​​<br />Abstract: Vi samlar personer på Matematiska vetenskaper och på Institutionen för fysik som är intresserade av utveckling av och forskning kring lärande. Målet med seminariet är att börja dela erfarenheter och lära av varandra samt finna former för att fortsätta samverka. https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Computational221207.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Computational221207.aspxComputational and Applied Mathematics (CAM) seminar<p>MV:L14 and Zoom</p><p>​​Jan S Hesthaven, EPFL: Digital Twins through Reduced Order Models and Machine Learning</p>​<br />Abstract: The vision of building digital twins for complex infrastructure and systems is old. However, realizing it remains very challenging due to the need to combine advanced computational modeling, reduced order models, data infusion for calibration, updating and uncertainty management, and sensor integration to obtain models with true predictive value for decision support. Nevertheless, the perspectives of using digital twins for predictive maintenance, operational optimization, and risk analysis are very substantial and the potential for impact significant, from safety, planning, and financial points of view. <div>In this talk we shall first discuss the importance of reduced models in the development of digital twin technologies and continue by discussing different aspects of the challenges associated with developing digital twins through a few examples, combining advanced model and data driven technologies, e.g., classifiers, Gaussian regression and neural networks, to enable failure analysis, optimal sensor placement and, time permitting, multi-fidelity methods and risk analysis for rare events. </div> <div>These are all elements of the workflow that needs to be realized to address the challenge of building predictive digital twins and we shall demonstrated the value of such technologies through a number of different examples of increasing complexity.</div>https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Provforelasningar221208.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Provforelasningar221208.aspxProvföreläsningar, lektorat i algebra och geometri<p>Pascal, Mallvinden (zoom)</p><p>​Lars Kühne, Lars Martin Sektnan, Shuntaro Yamagishi</p>​​<br />9.00 Lars Kühne (Pascal)<p></p> <p>10.00 Lars Martin Sektnan (Pascal)</p> <p> 14.30 Shuntaro Yamagishi (på zoom). Lärarförslagsnämnden kommer att sitta på Mallvinden vid denna provföreläsning. Det finns några extra platser där för dem som vill se på storskärm, men alla intresserade kan följa föreläsningen på zoom: <a href="https://gu-se.zoom.us/j/65729952293">https://gu-se.zoom.us/j/65729952293</a></p> <p>Själva föreläsningen är ca 20 minuter, den börjar 10 minuter efter angiven tid, och sedan är det 10 minuter för frågor från Lärarförslagsnämnden och övriga närvarande. Ämnet är &quot;An introduction to Green's and Stokes' theorems&quot;</p> https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Statistics221208.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Statistics221208.aspxStatistics seminar<p>MV:L14, Chalmers tvärgata 3</p><p>​​Karin Hårding and Daire Carroll, University of Gothenburg: Population dynamics and ecology of seal populations, empirical data and the search for theory to help our understanding. Stochastic growth models, image analysis, spatial distribution and telemetry data on migrations</p>​​<br />Abstract: This talk is about how statistical and mathematical methods are helpful when we try to understand processes in wildlife populations. The European harbour seal (Sw: knubbsälen) has been studied carefully for 40 years and the long time series allows analysis of how population growth is regulated. Recently the population growth has declined and we visited the colonies to try to document in detail what is going on in order to give better advise to managers. We develop new methods for estimating body size from drones and for counting seals from photos with machine learning algorithms. We apply stochastic population growth models, dynamic energy budget models, and we discuss what is density dependence in age structured populations in a variable environment. We are also interested in new collaborations and feed back and look forward to interesting discussions on ways forward. Welcome! Karin and Dairehttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Statistics221215.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Statistics221215.aspxStatistics seminar<p>MV:L14, Chalmers tvärgata 3</p><p>Johan Jonasson, Chalmers University and University of Gothenburg: Noise sensitivity/stability for deep Boolean neural nets</p><br />Abstract: A well-known and ubiquitous property of neural net classifiers is that they can be fooled into misclassifying some objects by changing the input in tiny ways that are indistinguishable for the human eye. These changes can be adversarial, but sometimes they can be just random noise. This makes it interesting to ask if this property is something that almost all neural nets have and, when they do, why that is. There are good heuristic explanations, but to prove mathematically rigorous results seems very difficult in general. Here we prove some first results on various toy models. We treat our questions within the framework of the established field of noise sensitivity/stability. What we prove can roughly be stated as: <div><ul><li>A sufficiently deep fully connected network with sufficiently wide layers and iid Gaussian weights is noise sensitive, i.e. an arbitrarily small random noise makes the predicted class of a binary input string before and after the noise is added virtually independent. If one imposes correlations on the weights corresponding to the same input features, this still holds unless the correlation is very close to 1. </li> <li>Neural nets consisting of only convolutional layers may or may not be noise sensitive and we present examples of both behaviours.</li></ul> </div>https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Pedagogiskt-seminarium221219.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Pedagogiskt-seminarium221219.aspxPedagogiskt seminarium<p>MV:L14 och Zoom</p><p>​Meike Akveld, ETH: TBA</p>https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Licentiatseminarium221220.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Licentiatseminarium221220.aspxLicentiatseminarium i biovetenskap<p>Pascal, Hörsalsvägen 1</p><p>​David Lund: Computational discovery of antibiotic resistance genes and their horizonal transfer</p>​<br />Diskussionsinledare: professor Thomas Nordahl Petersen, Danmarks Tekniske Universitet<br />https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Disputation230119.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Disputation230119.aspxDisputation i matematik<p>Pascal, Hörsalsvägen 1</p><p>​Stepan Maximov: Infinite-dimensional Lie bialgebras and Manin pairs</p>​<br />Opponent: professor Volodymyr Mazorchuk, Uppsala universitethttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Disputation230120.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Disputation230120.aspxDisputation i matematik<p>Pascal, Hörsalsvägen 1</p><p>​Kristian Holm: Limit Theorems for Lattices and L-functions</p>​<br />Opponent: professor Florent Jouve, Université de Bordeaux, Frankrikehttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/nordstat-2023.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/nordstat-2023.aspx29th Nordic Conference in Mathematical Statistics<p>Kemihuset, Kemigården 4</p><p>​(NORDSTAT 2023)</p>​​<br />NORDSTAT will be an in-person conference consisting of plenary lectures, invited and contributed talks, and a poster session. A preliminary program is available.