github.com/automl/ParameterImportance
automl/ParameterImportance
Parameter Importance Analysis Tool (⭐ 77)
arxiv.org/abs/1910.03632v6
Distilling Importance Sampling for Likelihood Free Inference
Likelihood-free inference involves inferring parameter values given observed data and a simulator model. The simulator is computer code which takes parameters, performs stochastic calculations, and outputs simulated data. In this work, we view the si...
arxiv.org/abs/2511.11236v3
Parameter-Efficient MoE LoRA for Few-Shot Multi-Style Editing
In recent years, image editing has garnered growing attention. However, general image editing models often fail to produce satisfactory results when confronted with new styles. The challenge lies in how to effectively fine-tune general image editing...
arxiv.org/abs/1512.06314v1
Maximizing diversity in biology and beyond
Entropy, under a variety of names, has long been used as a measure of diversity in ecology, as well as in genetics, economics and other fields. There is a spectrum of viewpoints on diversity, indexed by a real parameter q giving greater or lesser imp...
arxiv.org/abs/2505.11112v1
Relativistic regularized kappa distributions
The special relativistic generalization of isotropic regularized kappa distributions is derived and compared to that of the original Olbertian (or standard) kappa distributions. It is demonstrated that for the latter the kappa parameter is even stron...
arxiv.org/abs/2202.09636v2
Models with (broken) Z2 symmetries
I discuss the allowed parameter space as well as collider prospects of several new physics models containing (broken) Z2 symmetries. I focus on effects of current constraints on these, and touch on several future collider options....
www.reddit.com/r/LocalLLaMA/comments/1qbpz5l/kyutai_just_introduced_pocket_tts_a_100mparameter/
kyutai just introduced Pocket TTS: a 100M-parameter text-to-speech model with hi…
Blog post with demo: Pocket TTS: A high quality TTS that gives your CPU a voice: [https://kyutai.org/blog/2026-01-13-pocket-tts](https://kyutai.org/blog/2026-01-13-pocket-tts) GitHub: [https://github...
arxiv.org/abs/2012.10337v2
The half-space Airy stat process
We study the multipoint distribution of stationary half-space last passage percolation with exponentially weighted times. We derive both finite-size and asymptotic results for this distribution. In the latter case we observe a new one-parameter proce...
arxiv.org/abs/1509.02882v2
Least Squares Shadowing method for sensitivity analysis of differential equation…
For a parameterized hyperbolic system $\frac{du}{dt}=f(u,s)$ the derivative of the ergodic average $\langle J \rangle = \lim_{T \to \infty}\frac{1}{T}\int_0^T J(u(t),s)$ to the parameter $s$ can be computed via the Least Squares Shadowing algorithm (...
arxiv.org/abs/1911.06015v1
Robust Parameter-Free Season Length Detection in Time Series
The in-depth analysis of time series has gained a lot of research interest in recent years, with the identification of periodic patterns being one important aspect. Many of the methods for identifying periodic patterns require time series' season len...
arxiv.org/abs/2507.05694v1
Bifurcation in dynamic problems with seasonal succession
We investigate the bifurcation structure of equilibria in a class of non-autonomous ordinary differential equations governed by a season length parameter, $τ$, which determines the alternation between growth and decline dynamics. This structure mode...
arxiv.org/abs/1808.04540v1
A Ramsey-type theorem for the matching number regarding connected graphs
A major line of research is discovering Ramsey-type theorems, which are results of the following form: given a graph parameter $ρ$, every graph $G$ with sufficiently large $ρ(G)$ contains a `well-structured' induced subgraph $H$ with large $ρ(H)$....
arxiv.org/abs/2010.16416v2
KiDS-1000 Cosmology: constraints beyond flat $Λ$CDM
We present constraints on extensions to the flat $Λ$CDM cosmological model by varying the spatial curvature $Ω_K$, the sum of the neutrino masses $\sum m_ν$, the dark energy equation of state parameter $w$, and the Hu-Sawicki $f(R)$ gravity $f_{R0...
arxiv.org/abs/1611.07531v2
Effects of waveform model systematics on the interpretation of GW150914
Parameter estimates of GW150914 were obtained using Bayesian inference, based on three semi-analytic waveform models for binary black hole coalescences. These waveform models differ from each other in their treatment of black hole spins, and all thre...
arxiv.org/abs/0903.0423v1
Lowered Nonextensive Stellar Distribution
The structure of globular clusters and elliptical galaxies are described in an unified way through a new class of lowered models inspired on the nonextensive kinetic theory. These power law models are specified by a single parameter q which quantif...
www.bing.com/ck/a?!&&p=277fe33a4102b108f3c0a9a4a7e49d8bde8124353e3c6b05bb82639ca043cfdbJmltdHM9MTc3MjU4MjQwMA&ptn=3&ver=2&hsh=4&fclid=0d02a40a-99f3-6902-3f71-b3199879680d&u=a1aHR0cHM6Ly9haS5zdGFja2V4Y2hhbmdlLmNvbS9xdWVzdGlvbnMvNTc2OS9pbi1hLWNubi1kb2VzLWVhY2gtbmV3LWZpbHRlci1oYXZlLWRpZmZlcmVudC13ZWlnaHRzLWZvci1lYWNoLWlucHV0LWNoYW5uZWwtb3I&ntb=1
In a CNN, does each new filter have different weights for each input ...
Typically for a CNN architecture, in a single filter as described by your number_of_filters parameter, there is one 2D kernel per input channel. There are input_channels * number_of_filters sets of …
arxiv.org/abs/2205.14467v1
Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box…
Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain. It does not require access to both the source-domain data and the predictor parameter...
github.com/Nick-qsv/MLP-PPO-2PLY-MULTI
Nick-qsv/MLP-PPO-2PLY-MULTI
Backgammon neural network that learns by playing against itself. The neural net plays multiple backgammon games at once in parallel CPU processes, feeding training batches to a GPU to update the network weights. A shared parameter manager coordinates weight up…
arxiv.org/abs/1702.04347v1
Whipping of electrified visco-capillary jets in airflows
An electrified visco-capillary jet shows different dynamic behavior, such as cone forming, breakage into droplets, whipping and coiling, depending on the considered parameter regime. The whipping instability that is of fundamental importance for elec...
en.wikipedia.org/wiki/PaLM
PaLM - Wikipedia
PaLM (Pathways Language Model) is a 540 billion-parameter dense decoder-only transformer-based large language model (LLM) developed by Google AI. Researchers