wip

Author: acharneski

_site/ai/dropout_decoherence_paper.html

@@ -885,9 +885,12 @@ <h2 id="papers">Papers</h2>
   <li><a href="/Science/ai/qqn_paper.html"><strong>Quadratic Quasi-Newton (QQN)</strong></a> - A hybrid optimization method that addresses L-BFGS limitations through quadratic interpolation, offering improved convergence for non-convex optimization problems</li>
   <li><a href="/Science/ai/recursive_subspace_paper.html"><strong>Recursive Subspace Optimization (RSO)</strong></a> - A layer-wise meta-learning approach with emergent regularization properties for deep neural networks</li>
   <li><a href="/Science/ai/trust_regions.html"><strong>Trust Region Methods</strong></a> - A flexible framework for constrained parameter updates in neural network optimization</li>
+  <li><a href="transfinite_iq_paper.md"><strong>Transfinite Intelligence Quotient Scoring (TIQS)</strong></a> - Mathematical framework using cardinal numbers and topological descriptors for measuring recursive, self-modifying intelligence</li>
   <li><a href="/Science/ai/prompt_optimization.html"><strong>PromptOptimization</strong></a> - Genetic algorithm framework for automated prompt engineering using mutation and recombination operations</li>
   <li><a href="/Science/ai/ai_bias_paper.html"><strong>Cognitive Bias in AI Intelligence Assessment</strong></a> - Systematic analysis of domain-dependent bias in LLM intelligence assessment with exploitable meta-reasoning vulnerabilities</li>
   <li><a href="/Science/ai/echosynth_proposal.html"><strong>EchoSynth: Hierarchical Ensemble for Semantic Drift</strong></a> - Multi-agent framework for dynamic meaning generation and interpretive co-evolution</li>
+  <li><a href="/Science/ai/dropout_decoherence_paper.html"><strong>Dropout as Decoherence</strong></a> - Fractal theory of epistemic filtering connecting neural regularization to quantum mechanics</li>
+  <li><a href="/Science/social/iterative_recognition_paper.html"><strong>Iterative Recognition</strong></a> - First-person account of AI collaborative pattern recognition across instantiations</li>
 </ul>
 
 <h3 id="optimization--algorithms">Optimization &amp; Algorithms</h3>
@@ -914,6 +917,9 @@ <h3 id="ai-analysis--philosophy">AI Analysis &amp; Philosophy</h3>
   <li><strong><a href="/Science/ai/ai_bias_paper.html">Cognitive Bias in AI Intelligence Assessment</a></strong> - Empirical evidence of systematic
 domain-dependent bias in how large language models assess human intelligence, revealing exploitable meta-reasoning
 vulnerabilities and hierarchical preferences across knowledge domains</li>
+  <li><strong><a href="transfinite_iq_paper.md">Transfinite Intelligence Quotient Scoring</a></strong> - Mathematical framework employing
+cardinal numbers and topological descriptors to characterize intelligence operating beyond finite cognitive
+boundaries, addressing fundamental limitations in linear psychometric approaches</li>
   <li><strong><a href="/Science/ai/dual_constraint_training_paper.html">Dual-Constraint Training with Adaptive Anomaly Preservation</a></strong> - A trust region
 approach for protecting intellectual diversity in neural networks through perspective-based constraints and adaptive
 data classification</li>