Transformer trained on simulated IMU + encoder data to infer contact states across robot morphologies, with MMD adaptation and STM32 deployment.
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World model RL agent trained in PyBullet and deployed to STM32 for torque control with < 0.2 ms inference.
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Self-supervised Transformer deployed to embedded node for real-time power grid anomaly detection (AUC > 0.90).
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PPO agent trained to optimize EV charging control under relay timing, thermal, and fault constraints.
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EEG + IMU → Transformer → Action command. Visualizes attention maps and exports to ONNX.
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Architecture-level modifications to AlexNet for enhanced feature extraction and classification accuracy.
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Recursive algorithm for prime and composite root approximation using adaptive mean-based stepping (≤3% error).
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Explores convergence, divergence, and oscillatory behavior of functions as they approach infinity in ℝ and ℂ.
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Analyzes how atomic radius influences catalytic activation energy trends across first-row transition metals.
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