Papers

• Mixture of Geodesic Factor Analyzers on Riemannian Homogeneous Spaces (2026)
  Hengchao Chen et al.
  4.81
• High-dimensional ridgeless least squares interpolation under spiked covariance structures (2026)
  Zhijun Liu et al.
  4.81
• Winning by Peeking: Unenforced Budgets and Test-Set Selection Inflate Short-Budget AutoML Comparisons (2026)
  Guilin Zhang et al.
  4.81
• Decoupled Continuous-Time Reinforcement Learning via Hamiltonian Flow (2026)
  Minh Nguyen
  1.67
• Learnable Conformal Prediction with Context-Aware Nonconformity Functions for Robotic Planning and Perception (2025)
  Divake Kumar et al.
  1.39
• Remarks on stochastic cloning and delayed-state filtering (2025)
  Tara Mina et al.
  1.33
• Convergence Guarantees for Deep Epsilon Greedy Policy Learning (2021)
  Michael Rawson et al.
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• Path Planning Problem under non-probabilistic Uncertainty (2022)
  Keivan Shariatmadar
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• Selective Sampling and Imitation Learning via Online Regression (2023)
  Ayush Sekhari et al.
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• Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior (2023)
  Adam Block et al.
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• Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning (2024)
  Dylan J. Foster and Adam Block and Dipendra Misra
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• Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions (2024)
  Iskander Azangulov et al.
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• Autonomy in the Real-World: Autonomous Trajectory Planning for Asteroid Reconnaissance via Stochastic Optimization (2024)
  Kazuya Echigo et al.
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