Deep Dive Papers
Comprehensive guides covering theory, code examples, mental models, and interview preparation for mastering autonomous driving simulation.
Waymax Deep Dive
Core simulator architecture, data-driven simulation, metrics system, and evaluation framework for autonomous driving.
WOSAC Challenge Deep Dive
Sim Agents Challenge evaluation framework, realism metrics, and winning strategies from 2023-2025.
JAX Scaling RL Deep Dive
How to scale RL training across GPUs/TPUs using JAX primitives: jit, vmap, pmap, scan, and distributed PPO.
V-Max Framework Deep Dive
Complete RL training pipeline including ScenarioMax, observation design, and reward hierarchy for driving policies.
BehaviorGPT Deep Dive
State-of-the-art sim agent modeling with transformers, Next-Patch Prediction, and the 2024 WOSAC winner approach.
Sim-to-Real Gap Deep Dive
Bridging virtual and physical worlds: perception, actuation, and behavioral gaps with neural rendering and world models.
Long-Tail Scenarios Deep Dive
Safety-critical testing at scale: adversarial generation, scenario mining, and coverage metrics for AV validation.
Distributed Training Deep Dive
Scaling RL to billions of steps: PureJaxRL, actor-learner architectures, and GPU-accelerated simulation infrastructure.
Neural Rendering for AD
3D Gaussian Splatting, NeRF, NeuRAD, SplatAD, and differentiable rendering for photorealistic sensor simulation.
Synthetic Data for Perception
Data generation pipelines, domain randomization, auto-labeling, and domain gap mitigation for perception training.
Physics-Based Sensor Simulation
Camera, lidar, and radar physics modeling with ray tracing, Vulkan rendering engines, and multi-fidelity approaches.
World Models for AD
GAIA-1, Waymo World Model, DriveDreamer, and generative simulation as an alternative to reconstruction-based approaches.
Applied Intuition Platform
Complete platform analysis: Neural Sim, Synthetic Data, Sensor Sim, SDS autonomy stack, and competitive landscape.
Recommended Learning Path
For the best learning experience, we recommend reading the papers in order. Each paper builds upon concepts from the previous ones.
- 1Waymax Deep Dive
Core simulator architecture, data-driven simulation, metrics system, and evaluation framework for autonomous driving.
- 2WOSAC Challenge Deep Dive
Sim Agents Challenge evaluation framework, realism metrics, and winning strategies from 2023-2025.
- 3JAX Scaling RL Deep Dive
How to scale RL training across GPUs/TPUs using JAX primitives: jit, vmap, pmap, scan, and distributed PPO.
- 4V-Max Framework Deep Dive
Complete RL training pipeline including ScenarioMax, observation design, and reward hierarchy for driving policies.
- 5BehaviorGPT Deep Dive
State-of-the-art sim agent modeling with transformers, Next-Patch Prediction, and the 2024 WOSAC winner approach.
- 6Sim-to-Real Gap Deep Dive
Bridging virtual and physical worlds: perception, actuation, and behavioral gaps with neural rendering and world models.
- 7Long-Tail Scenarios Deep Dive
Safety-critical testing at scale: adversarial generation, scenario mining, and coverage metrics for AV validation.
- 8Distributed Training Deep Dive
Scaling RL to billions of steps: PureJaxRL, actor-learner architectures, and GPU-accelerated simulation infrastructure.
- 9Neural Rendering for AD
3D Gaussian Splatting, NeRF, NeuRAD, SplatAD, and differentiable rendering for photorealistic sensor simulation.
- 10Synthetic Data for Perception
Data generation pipelines, domain randomization, auto-labeling, and domain gap mitigation for perception training.
- 11Physics-Based Sensor Simulation
Camera, lidar, and radar physics modeling with ray tracing, Vulkan rendering engines, and multi-fidelity approaches.
- 12World Models for AD
GAIA-1, Waymo World Model, DriveDreamer, and generative simulation as an alternative to reconstruction-based approaches.
- 13Applied Intuition Platform
Complete platform analysis: Neural Sim, Synthetic Data, Sensor Sim, SDS autonomy stack, and competitive landscape.