HPO enables unbiased policy optimization in hybrid action spaces by mixing differentiable simulation gradients with score-function estimates, outperforming PPO as continuous dimensions increase.
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Difftaichi: Differentiable programming for physical simulation
12 Pith papers cite this work. Polarity classification is still indexing.
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Four continuous relaxations turn non-differentiable coverage and revisit calculations into a fully differentiable pipeline that optimizes satellite orbits via gradients and outperforms metaheuristics.
VertAX supplies a differentiable JAX implementation of vertex models for confluent epithelia that enables forward simulation, mechanical parameter inference, and inverse design of tissue-scale behaviors.
A vision-language framework generates text-based rigid-body scene configurations from videos using motion reasoning and optical flow, reporting 0.30 IoU on CLEVRER (7x over baselines) and transfer to 235 real videos.
COSMIC co-optimizes robot structure, materials, and control simultaneously via differentiable simulation and constrained gradients, yielding locomotion strategies that outperform sequential baselines.
RigidFormer learns mesh-free rigid dynamics from point clouds using object-centric anchors, Anchor-Vertex Pooling, Anchor-based RoPE, and differentiable Kabsch alignment to enforce rigidity.
PhysMorph-GS injects visual supervision via deformation gradients in differentiable physics simulation and uses phased Chamfer-guided plasticity to reduce silhouette error by up to 49.9% compared to physics-only baselines.
Introduces boundary-focused rollouts to screen the smoothing parameter κ and augments a discrete-time CBF with a fixed robust margin to eliminate contact force violations in smoothed implicit dynamics simulations.
OrbiSim builds a differentiable physics engine from world models to support gradient-based policy optimization and contact modeling in robotics.
Neural Control introduces adjoint-based differentiation through implicit equilibrium constraints to enable memory-efficient gradient computation and robust receding-horizon MPC for multi-stable deformable object manipulation, outperforming gradient-free baselines in simulation and hardware.
The authors develop a differentiable simulator enforcing Markovian dynamics on a position-velocity manifold and using a mass-aligned preconditioner with a soft Fischer-Burmeister operator to produce stable gradients for frictional contact in large-deformation scenarios.
citing papers explorer
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Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients
HPO enables unbiased policy optimization in hybrid action spaces by mixing differentiable simulation gradients with score-function estimates, outperforming PPO as continuous dimensions increase.
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Differentiable Satellite Constellation Configuration via Relaxed Coverage and Revisit Objectives
Four continuous relaxations turn non-differentiable coverage and revisit calculations into a fully differentiable pipeline that optimizes satellite orbits via gradients and outperforms metaheuristics.
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VertAX: a differentiable vertex model for learning epithelial tissue mechanics
VertAX supplies a differentiable JAX implementation of vertex models for confluent epithelia that enables forward simulation, mechanical parameter inference, and inverse design of tissue-scale behaviors.
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$\Delta$ynamics: Language-Based Representation for Inferring Rigid-Body Dynamics From Videos
A vision-language framework generates text-based rigid-body scene configurations from videos using motion reasoning and optical flow, reporting 0.30 IoU on CLEVRER (7x over baselines) and transfer to 235 real videos.
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COSMIC: Concurrent Optimization of Structure, Material, and Integrated Control for robotic systems
COSMIC co-optimizes robot structure, materials, and control simultaneously via differentiable simulation and constrained gradients, yielding locomotion strategies that outperform sequential baselines.
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RigidFormer: Learning Rigid Dynamics using Transformers
RigidFormer learns mesh-free rigid dynamics from point clouds using object-centric anchors, Anchor-Vertex Pooling, Anchor-based RoPE, and differentiable Kabsch alignment to enforce rigidity.
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PhysMorph-GS: Render-Guided Volumetric Morphing with Differentiable Physics
PhysMorph-GS injects visual supervision via deformation gradients in differentiable physics simulation and uses phased Chamfer-guided plasticity to reduce silhouette error by up to 49.9% compared to physics-only baselines.
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Safety-Critical Control for Smoothed Implicit Contact Dynamics
Introduces boundary-focused rollouts to screen the smoothing parameter κ and augments a discrete-time CBF with a fixed robust margin to eliminate contact force violations in smoothed implicit dynamics simulations.
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OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence
OrbiSim builds a differentiable physics engine from world models to support gradient-based policy optimization and contact modeling in robotics.
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Neural Control: Adjoint Learning Through Equilibrium Constraints
Neural Control introduces adjoint-based differentiation through implicit equilibrium constraints to enable memory-efficient gradient computation and robust receding-horizon MPC for multi-stable deformable object manipulation, outperforming gradient-free baselines in simulation and hardware.
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Fast and Reliable Gradients for Deformables Across Frictional Contact Regimes
The authors develop a differentiable simulator enforcing Markovian dynamics on a position-velocity manifold and using a mass-aligned preconditioner with a soft Fischer-Burmeister operator to produce stable gradients for frictional contact in large-deformation scenarios.
- Exploring the Boundaries of Differentiable Radiation Transport and Detector Simulation