Block-sequential updates on the SK model are exactly characterized by a system of integro-difference equations, conjectured to coincide with systematic scan dynamics as the block size vanishes.
Real analysis: modern techniques and their applications
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
representative citing papers
Defines responsive distributions for G-normal random variables and proposes a convergent coupled trinomial tree algorithm to compute G-expectations and sample the induced laws.
An automated market maker's adverse-selection cost (LVR) equals the funding fee of a replicating portfolio of perpetual continuous-installment puts, enabling forward-looking LVR estimation and liquidity-band design.
AGMCTS augments MCTS with action-score gradients for particle beliefs, a Multiple Importance Sampling tree for reuse, and Area Formula gradients for smooth models, outperforming prior sample-based solvers on continuous benchmarks.
A multi-frequency regularization method and a spectral covariance method are proposed to recover source terms in stochastic Helmholtz and finite-jump Lévy-driven wave equations from final-time observations.
Under linearity and a continuity assumption, every feature attribution method is an integral against a signed measure, so the design choice reduces to picking the measure.
citing papers explorer
-
Sequential Dynamics in Ising Spin Glasses
Block-sequential updates on the SK model are exactly characterized by a system of integro-difference equations, conjectured to coincide with systematic scan dynamics as the block size vanishes.
-
Responsive Distribution of G-normal Random Variables
Defines responsive distributions for G-normal random variables and proposes a convergent coupled trinomial tree algorithm to compute G-expectations and sample the induced laws.
-
Modeling Loss-Versus-Rebalancing in Automated Market Makers via Continuous-Installment Options
An automated market maker's adverse-selection cost (LVR) equals the funding fee of a replicating portfolio of perpetual continuous-installment puts, enabling forward-looking LVR estimation and liquidity-band design.
-
Action-Gradient Monte Carlo Tree Search for Non-Parametric Continuous (PO)MDPs
AGMCTS augments MCTS with action-score gradients for particle beliefs, a Multiple Importance Sampling tree for reuse, and Area Formula gradients for smooth models, outperforming prior sample-based solvers on continuous benchmarks.
-
Inverse source problems for the stochastic wave equations
A multi-frequency regularization method and a spectral covariance method are proposed to recover source terms in stochastic Helmholtz and finite-jump Lévy-driven wave equations from final-time observations.
-
Feature Attribution from First Principles
Under linearity and a continuity assumption, every feature attribution method is an integral against a signed measure, so the design choice reduces to picking the measure.