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he Extinction Equation: What Happens When Advection Goes Too Far?
The paper introduces a nonlocal reaction-diffusion-advection problem in a bounded region with Dirichlet/Neumann boundary condition...
The Simple River Measurement That Predicts Ecosystem Collapse
This study illustrates the impact of advection speeds on the survival or demise of freshwater species in river ecosystems using nu...
The Mathematics of Life and Death
In order to examine the spatial dynamics of freshwater species in river habitats, this study creates a nonlocal reaction-diffusion...
The Math Behind Persistence and Extinction in Freshwater Ecosystems
The spatial dynamics of freshwater organisms in rivers with directed flow are examined in this research using a nonlocal reaction-...
Inside the Fake Dev Job Interview Industry
How I spent one day as a recruiter for fake dev job interviews.
The Geek’s Guide to ML Experimentation
We use tabular datasets originally from OpenML and compiled into a set of benchmark datasets from the Inria-Soda team on HuggingFa...
Can PEAR Make Deep Learning Easier to Trust?
The potential and constraints of PEAR as a preliminary step toward explaining consensus in deep learning are discussed. The succe...
Consensus Loss Proves AI Can Be Both Accurate and Transparent
This section examines the function of PEAR's two loss terms, its link to linearity, and whether it generates trivial or tainted ex...
The Trade-Off Between Accuracy and Agreement in AI Models
This section analyzes PEAR's effectiveness by calculating consensus across six recognized explainer agreement measures, including...
Notes on Training Neural Networks for Consensus
This paper presents the first framework to deliberately train neural networks for accuracy and agreement between feature attributi...
New AI Study Tackles the Transparency Problem in Black-Box Models
The disagreement issue in post hoc feature attribution techniques is discussed in this study. Explainers like SHAP, LIME, and grad...
