Toward a General Theory for the Scaling and Universality of Thermal Responses in Biology
We developed a theory showing that under appropriate normalizations and rescalings, temperature response curves show a remarkably regular behavior and follow a general, universal law. The impressive universality of temperature response curves remained hidden due to various curve-fitting models not well-grounded in first principles. In addition, this framework has the potential to explain the origin of different scaling relationships in thermal performance in biology, from molecules to ecosystems. Here, we summarize the background, principles and assumptions, predictions, implications, and possible extensions of this theory.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Neural Scaling Laws Rooted in the Data Distribution
Deep neural networks exhibit empirical neural scaling laws, with error decreasing as a power law with increasing model or data size, across a wide variety of architectures, tasks, and datasets. This universality suggests…
Language ModelingLanguage ModellingField theory for optimal signal propagation in ResNets
Residual networks have significantly better trainability and thus performance than feed-forward networks at large depth. Introducing skip connections facilitates signal propagation to deeper layers. In addition, previous…
SensitivityWhen does Gaussian equivalence fail and how to fix it: Non-universal behavior of random features with quadratic scaling
A major effort in modern high-dimensional statistics has been devoted to the analysis of linear predictors trained on nonlinear feature embeddings via empirical risk minimization (ERM). Gaussian equivalence theory (GET) …
Phase transitions in in vivo or in vitro populations of spiking neurons belong to different universality classes
The "critical brain hypothesis" posits that neural circuitry may be tuned close to a "critical point" or "phase transition" -- a boundary between different operating regimes of the circuit. The renormalization group and …
Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos
We develop a mean-field theory of dropout as a perturbation of critical signal propagation at the edge of chaos, and show that it predicts a simple, no-cost change to standard practice: \emph{front-loaded} dropout schedu…