The Fragile Memory of Neural Networks, and the Metrics We Trust Post date March 19, 2026 Post author By Adam Optimizer Post categories In adam-optimizer, ai-model-stability, ai-training, catastrophic-forgetting, continual-learning-ai, machine-learning-evaluation, neural-networks-memory-loss, reinforcement-learning
Why Adam May Be Hurting Your Neural Network’s Memory Post date March 19, 2026 Post author By Adam Optimizer Post categories In adam-optimizer, ai-model-stability, ai-training, catastrophic-forgetting, continual-learning-ai, machine-learning-evaluation, neural-networks-memory-loss, reinforcement-learning
Measuring Catastrophic Forgetting in AI Post date March 18, 2026 Post author By Adam Optimizer Post categories In adam-optimizer, ai-model-stability, ai-training, catastrophic-forgetting, continual-learning-ai, machine-learning-evaluation, neural-networks-memory-loss, reinforcement-learning
Study Finds Optimizer Choice Significantly Impacts Model Retention Post date March 18, 2026 Post author By Adam Optimizer Post categories In adam-optimizer, ai-model-stability, ai-training, catastrophic-forgetting, continual-learning-ai, machine-learning-evaluation, neural-networks-memory-loss, reinforcement-learning
Does the Adam Optimizer Amplify Catastrophic Forgetting? Post date March 17, 2026 Post author By Adam Optimizer Post categories In adam-optimizer, ai-model-stability, ai-training, catastrophic-forgetting, continual-learning-ai, hackernoon-top-story, neural-networks-memory-loss, reinforcement-learning
CIL Methods Fail IIL: Why Existing Baselines Struggle with Model Promotion Post date November 12, 2025 Post author By Instancing Post categories In catastrophic-forgetting, cil-baselines, dynamic-networks, iil-benchmarking, knowledge-distillation, machine-learning, model-reproduction, rehearsal-methods
CIL Methods Fail IIL: Why Existing Baselines Struggle with Model Promotion Post date November 12, 2025 Post author By Instancing Post categories In catastrophic-forgetting, cil-baselines, dynamic-networks, iil-benchmarking, knowledge-distillation, machine-learning, model-reproduction, rehearsal-methods
KC-EMA Mechanism: Theoretical Analysis and Derivation for IIL Post date November 7, 2025 Post author By Instancing Post categories In catastrophic-forgetting, gradient-derivation, instance-incremental-learning, knowledge-consolidation, machine-learning, model-ema, teacher-student-model, theoretical-analysis
SAGE Net Ablation Study: Analyzing the Impact of Input Sequence Length on Performance Post date November 5, 2025 Post author By Instancing Post categories In catastrophic-forgetting, cifar-100, imagenet-100, instance-incremental-learning, machine-learning, model-promotion, rehearsal-methods, sota-comparison
SAGE Net Ablation Study: Analyzing the Impact of Input Sequence Length on Performance Post date November 5, 2025 Post author By Instancing Post categories In catastrophic-forgetting, cifar-100, imagenet-100, instance-incremental-learning, machine-learning, model-promotion, rehearsal-methods, sota-comparison
Evaluating Instance-Incremental Learning: CIL Methods on Cifar-100 and ImageNet Post date November 5, 2025 Post author By Instancing Post categories In breeds-entity-30, catastrophic-forgetting, cifar-100, fine-tuning, imagenet-100, instance-incremental-learning, machine-learning, model-promotion-metrics
Evaluating Instance-Incremental Learning: CIL Methods on Cifar-100 and ImageNet Post date November 5, 2025 Post author By Instancing Post categories In breeds-entity-30, catastrophic-forgetting, cifar-100, fine-tuning, imagenet-100, instance-incremental-learning, machine-learning, model-promotion-metrics
Model Promotion: Using EMA to Balance Learning and Forgetting in IIL Post date November 5, 2025 Post author By Instancing Post categories In ai-models, catastrophic-forgetting, exponential-moving-average, instance-incremental-learning, knowledge-consolidation, model-generalization, overfitting-mitigation, teacher-student-model
Optimizing SAGE Net: Achieving High Performance with Shorter Input Sequences for Online Inference Post date November 5, 2025 Post author By Instancing Post categories In catastrophic-forgetting, db-center, dbd, decision-boundary, instance-incremental-learning, inter-class-interference, knowledge-distillation, sage-net
Incremental Learning: Comparing Methods for Catastrophic Forgetting and Model Promotion Post date November 4, 2025 Post author By Instancing Post categories In catastrophic-forgetting, class-incremental-learning, continual-domain-adaptation, continual-learning-methods, data-science, instance-incremental-learning, knowledge-distillation, rehearsal-methods
Data Scarcity Solution: S-CycleGAN for CT-to-Ultrasound Translation Post date November 4, 2025 Post author By Instancing Post categories In catastrophic-forgetting, concept-drift, continual-learning, data, data-scarcity, instance-incremental-learning, model-promotion, teacher-student-model
Data Scarcity Solution: S-CycleGAN for CT-to-Ultrasound Translation Post date November 4, 2025 Post author By Instancing Post categories In catastrophic-forgetting, concept-drift, continual-learning, data, data-scarcity, instance-incremental-learning, model-promotion, teacher-student-model
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