How an Open Model and a Pile of Data are Changing Time Series Analysis Post date June 30, 2025 Post author By Reinforcement Technology Advancements Post categories In causal-forecasting, low-supervision-time-series, moment-foundation-model, multi-dataset-pretraining, open-science-time-series, time-series-foundation-models, time-series-pile, time-series-transparency
When a Specialized Time Series Model Outshines General LLMs Post date June 30, 2025 Post author By Reinforcement Technology Advancements Post categories In cross-modal-time-series, limited-supervision-ts, linear-probing-time-series, moment-benchmark, time-series-interpretability, time-series-model-scaling, ucr-anomaly-detection, zero-shot-forecasting
How Do You Train an AI to Understand Time? With a Giant Pile of Data. Post date June 30, 2025 Post author By Reinforcement Technology Advancements Post categories In downstream-task-fine-tuning, foundation-model-pretraining, hackernoon-top-story, instance-normalization-ts, masked-time-series-modeling, multi-dataset-training, time-series-patching, time-series-pile
Why Training on Time Series Beats Fine-Tuning LLMs for Time Series Tasks Post date June 30, 2025 Post author By Reinforcement Technology Advancements Post categories In contrastive-vs-masked, cross-modal-transfer-learning, llm-for-time-series, masked-time-series-modeling, multi-dataset-pretraining, time-foundation-models, time-series-patching, zero-shot-time-series
How a New AI Model is Taming the Chaos of Time Series Data Post date June 30, 2025 Post author By Reinforcement Technology Advancements Post categories In few-shot-time-series, foundation-models, masked-time-series-modeling, moment-foundation-model, multi-datasets-time-series, time-series-pile, time-series-pretraining, zero-shot-forecasting
GPT-2 Architecture and Training Details: Parameters & Cross-Entropy Loss Post date June 24, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Theoretical Derivations: Cross-Entropy Loss and Energy Functions in LLMs Post date June 24, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
LogSumExp Function Properties: Lemmas for Energy Functions Post date June 24, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Transformer Performance: Hopfield Theory & Cross-Entropy Loss Data Post date June 24, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
New Regularization-Free Energy Function for Transformer Analysis Post date June 22, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Validating Theoretical Loss Bound: Vanilla Transformer Experiments Post date June 22, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
The Impact of Data Size on Transformer Training: Overfitting & Loss Dynamics Post date June 21, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Empirical Results: GPT-2 Analysis of Transformer Memorization & Loss Post date June 21, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Related Work: Scaling Laws and Hopfield Models in LLM Research Post date June 18, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Theoretical Framework: Transformer Memorization & Performance Dynamics Post date June 18, 2025 Post author By Reinforcement Technology Advancements Post categories In associative-memory, attention-mechanism, cross-entropy-loss, hopfield-networks, model-generalization, model-scaling, neural-network-performance, transformer-models
Continual Learning in Reinforcement Learning Agents with Pre-trained, Testing, and Untrained Groups Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continual-learning-group, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-based-agents, stylized-facts-in-finance
Reinforcement Learning Simulation Metrics: QQ plots, ACF graphs, and Volatility Analysis Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-based-agents, rl-simulation-metrics, stylized-facts-in-finance
RL Agents Show Superior Realism and Adaptability Over Zero-Intelligence Agents Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-based-agents, stylized-facts-in-finance, zero-intelligence-agents
Configuring Reinforcement Learning Simulation: Agent Settings, Hyper-Parameters, & Market Insights Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-based-agents, simulation-configuration, stylized-facts-in-finance
Reinforcement Learning Agents Optimizes Trading in CDA Markets Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, cda-markets, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-based-agents, stylized-facts-in-finance
Realistic Market Simulations Are Essential for Testing Reinforcement Learning Behavior Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, financial-market-modeling, machine-learning-in-finance, realistic-market-simulation, reinforcement-learning, rl-based-agents, stylized-facts-in-finance
Continual Learning RL Agents Set New Standard for Realistic Market Simulations Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continual-learning-rl-agents, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-based-agents, stylized-facts-in-finance
Market-Making & Liquidity-Taking Agents Leverages Independent Policies & Reward-driven Strategies Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, liquidity-taking, market-making, reinforcement-learning, rl-based-agents, stylized-facts-in-finance
RL Agents Adapt to Flash Sale Events & Imbalanced Limit Order Books (LOBs) Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-agent-responsiveness, rl-based-agents, stylized-facts-in-finance
Reinforcement Learning Simulation Features Realism and Adaptability Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, reinforcement-learning, rl-agents-system-description, rl-based-agents, stylized-facts-in-finance
Reinforcement Learning Revolutionizes Market Insights with Adaptive Simulations Post date January 1, 2025 Post author By Reinforcement Technology Advancements Post categories In agent-based-market-simulation, continuous-double-auction, financial-market-modeling, machine-learning-in-finance, market-dynamics, reinforcement-learning, rl-based-agents, stylized-facts-in-finance
Generalizing Deep Learning Models for Varied Diffusion Equations Post date June 21, 2024 Post author By Reinforcement Technology Advancements Post categories In deep-learning, deep-learning-benchmarks, diffusion-surrogate, encoder-decoder, multiscale-modeling, neural-network-architecture, neural-networks, training-algorithms
Optimizing Data Set Size and Loss Functions for Enhanced Neural Network Performance Post date June 21, 2024 Post author By Reinforcement Technology Advancements Post categories In deep-learning, deep-learning-benchmarks, diffusion-surrogate, encoder-decoder, multiscale-modeling, neural-network-architecture, neural-networks, training-algorithms
Understanding Factors Affecting Neural Network Performance in Diffusion Prediction Post date June 21, 2024 Post author By Reinforcement Technology Advancements Post categories In deep-learning, deep-learning-benchmarks, diffusion-surrogate, encoder-decoder, multiscale-modeling, neural-network-architecture, neural-networks, training-algorithms
Architecting Neural Networks for Diffusion Prediction: A Study on Encoder-Decoder CNNs Post date June 21, 2024 Post author By Reinforcement Technology Advancements Post categories In deep-learning, deep-learning-benchmarks, diffusion-surrogate, encoder-decoder, multiscale-modeling, neural-network-architecture, neural-networks, training-algorithms
Analyzing the Performance of Deep Encoder-Decoder Networks as Surrogates for a Diffusion Equation Post date June 21, 2024 Post author By Reinforcement Technology Advancements Post categories In deep-learning, deep-learning-benchmarks, diffusion-surrogate, encoder-decoder, multiscale-modeling, neural-network-architecture, neural-networks, training-algorithms
The Future of AI in Finance Post date June 16, 2024 Post author By Reinforcement Technology Advancements Post categories In automated-trading-in-finrl, blockchain-api, crypto-api, cryptocurrency-trading, deep-reinforcement-learning, drl-algorithms, drl-in-finance, quantitative-finance
FinRL’s Implementation of DRL Algorithms for Stock Trading Post date June 16, 2024 Post author By Reinforcement Technology Advancements Post categories In ai-in-finance, automated-trading-in-finrl, crypto-api, cryptocurrency-trading, deep-reinforcement-learning, drl-algorithms, financial-market-simulation, quantitative-finance
End-to-End Solutions for Cryptocurrency Trading Post date June 16, 2024 Post author By Reinforcement Technology Advancements Post categories In ai-in-finance, crypto-api, cryptocurrency-trading, deep-reinforcement-learning, drl-algorithms, financial-market-simulation, quantitative-finance, sharpe-ratio
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