IDTIMWYTIM: Stochasticity - THAT'S Random
Hank helps us understand the difference between the colloquial meaning of randomness, and the scientific meaning, which is also known as stochasticity. We will learn how, in fact, randomness is surprisingly predictable. Like SciShow: http://www.facebook.com/scishow Follow SciShow: http://
From playlist Uploads
Introduction to the paper https://arxiv.org/abs/2002.06707
From playlist Research
Basic stochastic simulation b: Stochastic simulation algorithm
(C) 2012-2013 David Liao (lookatphysics.com) CC-BY-SA Specify system Determine duration until next event Exponentially distributed waiting times Determine what kind of reaction next event will be For more information, please search the internet for "stochastic simulation algorithm" or "kin
From playlist Probability, statistics, and stochastic processes
Eulalia Nualart: Asymptotics for some non-linear stochastic heat equations
Abstract: Consider the following stochastic heat equation, ∂ut(x)/∂t = −ν(−Δ)α/2ut(x)+σ(ut(x))F˙(t,x),t[is greater than]0,x∈ℝd. Here −ν(−Δ)α/2 is the fractional Laplacian with ν[is greater than]0 and α∈(0,2], σ:ℝ→ℝ is a globally Lipschitz function, and F˙(t,x) is a Gaussian noise which is
From playlist Probability and Statistics
Hybrid sparse stochastic processes and the resolution of (...) - Unser - Workshop 2 - CEB T1 2019
Michael Unser (EPFL) / 12.03.2019 Hybrid sparse stochastic processes and the resolution of linear inverse problems. Sparse stochastic processes are continuous-domain processes that are specified as solutions of linear stochastic differential equations driven by white Lévy noise. These p
From playlist 2019 - T1 - The Mathematics of Imaging
Fluctuation theorem for entropy production of a partial by Sanjib Sabhpandit
Stochastic Thermodynamics, Active Matter and Driven Systems DATE: 07 August 2017 to 11 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore. Stochastic Thermodynamics and Active Systems are areas in statistical physics which have recently attracted a lot of attention and many intere
From playlist Stochastic Thermodynamics, Active Matter and Driven Systems - 2017
Francois Baccelli: High dimensional stochastic geometry in the Shannon regime
This talk will focus on Euclidean stochastic geometry in the Shannon regime. In this regime, the dimension n of the Euclidean space tends to infinity, point processes have intensities which are exponential functions of n, and the random compact of interest sets have diameters of order squa
From playlist Workshop: High dimensional spatial random systems
Davide Gabrielli : Macroscopic fluctuation theory / Particle systems, scaling limits and...
Abstract: In this first lecture I will introduce a class of stochastic microscopic models very useful as toy models in non equilibrium statistical mechanics. These are multi-component stochastic particle systems like the exclusion process, the zero range process and the KMP model. I will d
From playlist Mathematical Physics
Stochastic processes by VijayKumar Krishnamurthy
Winter School on Quantitative Systems Biology DATE: 04 December 2017 to 22 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The International Centre for Theoretical Sciences (ICTS) and the Abdus Salam International Centre for Theoretical Physics (ICTP), are organizing a Wint
From playlist Winter School on Quantitative Systems Biology
New Directions in the Statistical Mechanics of Turbulence by Nigel Goldenfeld
PROGRAM TURBULENCE: PROBLEMS AT THE INTERFACE OF MATHEMATICS AND PHYSICS ORGANIZERS Uriel Frisch (Observatoire de la Côte d'Azur and CNRS, France), Konstantin Khanin (University of Toronto, Canada) and Rahul Pandit (IISc, India) DATE & TIME 16 January 2023 to 27 January 2023 VENUE Ramanuj
From playlist Turbulence: Problems at the Interface of Mathematics and Physics 2023
Stochastic Approach to Non-Equilibrium Quantum Spin Systems by Joe Bhaseen
PROGRAM NON-HERMITIAN PHYSICS - PHHQP XVIII DATE :04 June 2018 to 13 June 2018 VENUE:Ramanujan Lecture Hall, ICTS Bangalore Non-Hermitian Physics-"Pseudo-Hermitian Hamiltonians in Quantum Physics (PHHQP) XVIII" is the 18th meeting in the series that is being held over the years in Qua
From playlist Non-Hermitian Physics - PHHQP XVIII
"Diffusion Approximation and Sequential Experimentation" by Victor Araman
We consider a Bayesian sequential experimentation problem. We identify environments in which the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regimes, we derive a diffusion approximation f
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
Integrating Inference with Stochastic Process Algebra Models - Jane Hillston, Edinburgh
ProPPA is a probabilistic programming language for continuous-time dynamical systems, developed as an extension of the stochastic process algebra Bio-PEPA. It offers a high-level syntax for describing systems of interacting components with stochastic behaviours where some of the parameters
From playlist Logic and learning workshop
Tipping in Spatial Systems (Lecture 1) by Vishwesha Guttal
PROGRAM TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID) ORGANIZERS: Partha Sharathi Dutta (IIT Ropar, India), Vishwesha Guttal (IISc, India), Mohit Kumar Jolly (IISc, India) and Sudipta Kumar Sinha (IIT Ropar, India) DATE: 19 September 2022 to 30 September 2022 VENUE: Ramanujan Lecture Hall an
From playlist TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID, 2022)
Non-stationary Markow Processes: Approximations and Numerical Methods by Peter Glynn
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Applied Math Perspectives on Stochastic Climate Models ( 2 ) - Andrew J. Majda
Lecture 2: Applied Math Perspectives on Stochastic Climate Models Abstract: We are entering a new era of Stochastic Climate Modeling. Such an approach is needed for several reasons: 1) to model crucial poorly represented processes in contemporary comprehensive computer models such as inte
From playlist Mathematical Perspectives on Clouds, Climate, and Tropical Meteorology
Stochastic Analysis and Applications in Gene Networks by Chunhe Li
PROGRAM TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID) ORGANIZERS: Partha Sharathi Dutta (IIT Ropar, India), Vishwesha Guttal (IISc, India), Mohit Kumar Jolly (IISc, India) and Sudipta Kumar Sinha (IIT Ropar, India) DATE: 19 September 2022 to 30 September 2022 VENUE: Ramanujan Lecture Hall an
From playlist TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID, 2022)
Silvia Villa - Generalization properties of multiple passes stochastic gradient method
The stochastic gradient method has become an algorithm of choice in machine learning, because of its simplicity and small computational cost, especially when dealing with big data sets. Despite its widespread use, the generalization properties of the variants of stochastic
From playlist Schlumberger workshop - Computational and statistical trade-offs in learning
Thermodynamics along individual quantum trajectories of qubit by Kater Murch
Open Quantum Systems DATE: 17 July 2017 to 04 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore There have been major recent breakthroughs, both experimental and theoretical, in the field of Open Quantum Systems. The aim of this program is to bring together leaders in the Open Q
From playlist Open Quantum Systems