Book of abstracts
Plenary Lecture or Open Public Lecture
The cutoff phenomenon for Markov chains
On rates in the central limit theorem for a class of convex costs
Critical long-range percolation
On estimating Fr'{e}Chet means
What AI will not tell you about white noise
Exchangeability in Continuum Random Trees
Bootstrap percolation and kinetically constrained models: universality results
IS01: Statistics for Stochastic Processes
IS02: Heavy-Tailed Phenomena in Networks
Emergence of heavy-tailed cascades in flow networks through a unified stochastic overload framework.
IS03: Self-Organized Criticality
The particle density in mean-field Activated Random Walk and the 2D sandpile
IS04: Geometry of Random Walks
IS05: Random Planar Geometry
Percolation of Gaussian free field and loop soup in dimension two
IS06: Lévy-Type Processes
IS07: Inhomogeneous Spatial Graph Models
IS08: Emerging Topics in Stochastic Finance
Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks
IS09: Random Partitions
IS10: Martingales and Their Applications in PDEs and Harmonic Analysis
IS11: Long Range Percolation Models
Hausdorff dimension of the critical clusters for the metric graph Gaussian free field
IS12: Superlinear Stochastic Partial Differential Equations
IS13: Recent Developments in Branching Structures
IS14: Probabilistic Aspects of Data Privacy
IS15: Extremes of Gaussian and Related Random Fields
IS16: Stochastic Stability
Poisson Hail on a Wireless Ground
IS17: Applications of Stochastic Analysis to Deep Learning
The Proportional Scaling Limit of Neural Networks
IS18: SDEs: Analysis, Approximation, Inference
Feynman-Kac formula for the gradient of the Dirichlet problem and its applications
A Tail-Respecting Explicit Numerical Scheme for Lévy-Driven SDEs With Superlinear Drifts
Statistical inference for locally stable regression
IS19: Branching and Interacting Particle Systems
Discounted tree sums in branching random walks
IS20: Non-Equilibrium Statistical Mechanics
Collisions of the supercritical Keller-Segel particle system
Stochastic and dynamical approaches to non-Hermitian matrix-valued processes
IS21: On Nodal Random Variables
IS22: Probabilistic Foundations of Machine Learning
IS23: Inference in Stochastic Networks
Inference in dynamic random graphs
Inference in infinite-server queueing networks with Poisson sampling
IS24: Random Media and Limit Theorems
IS25: Quasi-Stationary Distributions and Applications
IS26: Invariant Measures and Scaling Limits of Integrable Systems
Simple nonlinear PDEs inspired by billiards
IS27: Rough Analysis
IS28: Random Matrices and Combinatorial Structures
The spectrum of dense kernel-based random graphs
IS29: Probabilistic and Statistical Study of Systems of Interacting Neurons
Nonparametric estimation of the jump rate in mean field interacting systems of neurons
Asymptotic behaviour of networks of Hopfield-like neurons
IS30: Mixing Times for Random Walks
IS31: Random Growth and KPZ Universality
Scaling limit of half-space KPZ equation
IS32: Stochastic Eco-Evolutionary Models
Convergence of a general structured individual-based model with possibly unbounded growth, birth and death rates
CS01: Advanced Bayesian Methods and Statistical Innovations in High-Dimensional Mixed-Type Data Analysis and Neuroimaging
Bayesian Sparse Kronecker Product Decomposition for Multi-task Mixed-effects Regression with Tensor Predictors
Low-rank regularization of Fréchet regression models for distribution function response
CS02: Recent Progress on Stein’s Method
High-dimensional bootstrap and asymptotic expansion
Brownian approximation for deterministic dynamical systems: a Stein’s method approach
Normal approximation for exponential random graphs
CS03: Renormalization in Probability and Quantum Field Theory
CS04: Branching Processes as Models for Structured Populations
CS05: Recent Advances in Interacting Brownian Particle Systems and Their Mean-Field Limits
Convex order and increasing convex order for McKean-Vlasov processes with common noise
CS06: Control and Estimation in Stochastic Systems
Goggin’s corrected Kalman Filter: Guarantees and Filtering Regimes
CS07: Stochastic Properties of Time-Dependent Random Fields
CS08: New Frontiers in Stochastic Quantisation
CS09: Limit Theorems Through the Lens of Wiener Chaos and Stein-Malliavin Techniques
CS10: Dynamics of Stochastic Particle Systems
CS11: Community Detection on Random Network Models
Optimality of a barrier strategy in a spectrally negative Lévy model with a level-dependent intensity of bankruptcy
CS12: Recent Advances in Non-Markovian Processes and Random Fields
Sample path properties of Gaussian random fields with slowly varying increments
Fourier dimension of the graph of fractional Brownian motion with H>1/2
Scaling limit of dependent random walks
CS13: Complex Systems I
Langevin equation in quenched heterogeneous landscapes
CS14: Complex Systems II
CS15: Complex Systems III
CS16: Recent Advances in Financial and Actuarial Mathematics
Valuation of multi-region CoCoCat bonds
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CS17: Dependent Percolation Models: Discrete and Continuum
Percolation in lattice k-neighbor graphs
CS18: Recent Advances in Generalised Preferential Attachment Models
CS19: Reinforcement Models: Elephant Random Walk
Some results for variations of the Elephant random walk
Step Reinforced Random Walks with Regularly Varying Memory
CS20: Parameter Randomization Methods for Stochastic Processes
Anomalous diffusive processes with random parameters. Theory and Applications.
Lévy processes with values in the cone of non-negatively defined matrices
CS21: Stochastic Numerics on Manifolds
Kinetic Langevin equations on Lie groups with a geometric mechanics approach
CS22: Noncommutative Stochastic Processes
Stochastic optimization in free probability
CS23: Stochastic Processes Under Constraints
Persistence of Strongly Correlated Stationary Gaussian fields: From Universal Probability Decay to Entropic Repulsion
CS24: Recent Advances in Statistical Inference for Nonstationary Stochastic Processes
Statistical Properties of Oscillatory Processes with Stochastic Modulation in Amplitude and Time
Spectral analysis of harmonizable processes with spectral mass concentrated on lines
CS25: Volterra Gaussian Processes
CS26: Inference for Stochastic Equations
Parameter estimation for SDEs with Rosenblatt noise
Statistical inference for semi-linear SPDEs using spatial information
CS27: Global and Non-Global Solutions of Semilinear Fractional Differential Equations
Global and Non-global Solutions of a Fractional Reaction-Diffusion Equation Perturbed by a Fractional Noise
On the explosion time of a semilinear stochastic partial differential equations driven by a mixture of Brownian and fractional Brownian motion
CS28: Propagation of Chaos in Life Science Models
Strong propagation of chaos for systems of interacting particles with nearly stable jumps
CS29: Computing the Invariant Distribution of Linear and Non-Linear Diffusions by Ergodic Simulation
Approximation of the invariant distribution for a class of ergodic jump diffusions
CS30: Gaussian Processes for Fractional Dynamics and Limiting Behaviour
Fractional rough diffusion Bessel processes: reflection, asymptotic behavior and parameter estimation
CS31: Extremes, Sojourns and Related Functionals of Gaussian Processes
On a Weak Convergence Theorem for the Normalized Maximum of Stationary Gaussian Processes with a Trend
CS32: Advances in Statistical Inference for Spatial Point Processes
Minimax Estimation of the Structure Factor of Spatial Point Processes
CS33: LLMs and ML in Dynamic Risk Control
LLM-Driven Stock Movement Prediction
CS34: Non-Local Operators in Probability: Anomalous Transport, Stochastic Resettings and Diffusions with Memory
CS35: Edge and Spectrum of Heterogeneous Ensembles
CS36: Probabilistic Graphical Models
SPA 2025
IS22: Probabilistic Foundations of Machine Learning
Organizer: Arnaud Guillin (Université Clermont Auvergne)