Update README.md

README.md

@@ -12,19 +12,13 @@ tags:
   - dave2
   - nvidia
 datasets:
-  - custom
+  - maxim-igenbergs/thesis-data
 ---
-
 # DAVE-2 End-to-End Driving Model
-
-Implementation of NVIDIA's DAVE-2 architecture trained on the Udacity self-driving car simulator for the bachelor's thesis: Dual-Axis Testing of Visual Robustness and Topological Generalization in Vision-based End-to-End Driving Models
-
+Implementation of NVIDIA's DAVE-2 architecture trained on the Udacity self-driving car simulator for the bachelor's thesis: Dual-Axis Testing of Visual Robustness and Topological Generalization in Vision-based End-to-End Driving Models.
 ## Model Description
-
 DAVE-2 is the original end-to-end driving architecture proposed by NVIDIA in 2016. It learns to map raw camera images directly to steering and throttle commands through imitation learning.
-
 ### Architecture
-
 ```
 Input: RGB Image (66 × 200 × 3)
     ↓
@@ -43,25 +37,19 @@ Dense(10) + ELU
     ↓
 Output: [steering, throttle]
 ```
-
 ## Checkpoints
-
 | Map | Checkpoint |
 |-----|------------|
 | GenRoads | `genroads_20251028-145557/` |
 | Jungle | `jungle_20251209-175046/` |
-
 ### Files per Checkpoint
-
 - `best_model.h5` — Keras model weights
 - `meta.json` — Training configuration and hyperparameters
 - `history.csv` — Training/validation metrics per epoch
 - `loss_curve.png` — Visualization of training progress
-
 ## Citation
-
 ```bibtex
-@thesis{igenbergs2025dualaxis,
+@thesis{igenbergs2026dualaxis,
   title={Dual-Axis Testing of Visual Robustness and Topological Generalization in Vision-based End-to-End Driving Models},
   author={Igenbergs, Maxim},
   school={Technical University of Munich},
@@ -69,10 +57,9 @@ Output: [steering, throttle]
   type={Bachelor's Thesis}
 }
 ```
-
 ## Related
-
 - [DAVE-2-GRU Driving Model](https://huggingface.co/maxim-igenbergs/dave2-gru)
 - [ViT Driving Model](https://huggingface.co/maxim-igenbergs/vit)
 - [TCP Driving Model](https://huggingface.co/maxim-igenbergs/tcp-carla-repro)
-- [Evaluation Runs Dataset](https://huggingface.co/datasets/maxim-igenbergs/thesis-runs)
+- [Training Data](https://huggingface.co/datasets/maxim-igenbergs/thesis-data)
+- [Evaluation Runs](https://huggingface.co/datasets/maxim-igenbergs/thesis-runs)