docs: add CHANGELOG.md to track releases

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: HFooladi

CHANGELOG.md

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+# Changelog
+
+All notable changes to this project will be documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [Unreleased]
+
+### Added
+
+### Changed
+
+### Fixed
+
+### Removed
+
+---
+
+## [0.2.0] - 2025-01-26
+
+### Added
+- **Evidential Deep Learning** (`molax/models/evidential.py`)
+  - `EvidentialGCN` model for single-pass uncertainty estimation
+  - Normal-Inverse-Gamma (NIG) loss function with configurable regularization
+  - Separate aleatoric and epistemic uncertainty outputs
+  - `evidential_uncertainty_sampling` and `combined_evidential_acquisition` functions
+  - Comprehensive tests and example script
+
+- **Deep Ensembles** (`molax/models/ensemble.py`)
+  - `DeepEnsemble` class with configurable number of members
+  - Separate epistemic (model disagreement) and aleatoric (data noise) uncertainty
+  - `ensemble_uncertainty_sampling` and `combined_ensemble_acquisition` functions
+  - Training utilities for ensemble members
+
+- Feature roadmap documentation (`docs/roadmap.md`)
+
+### Changed
+- Migrated to jraph for efficient graph batching (~400x speedup)
+- Updated to Flax NNX API (0.12+) with `nnx.List` for layer collections
+
+---
+
+## [0.1.0] - 2025-01-15
+
+### Added
+- Initial release
+- `MolecularGCN` and `UncertaintyGCN` models
+- MC Dropout uncertainty estimation
+- Basic acquisition functions: `uncertainty_sampling`, `diversity_sampling`, `combined_acquisition`
+- ESOL dataset support
+- SMILES to jraph graph conversion utilities
+
+---
+
+[Unreleased]: https://github.com/HFooladi/molax/compare/v0.2.0...HEAD
+[0.2.0]: https://github.com/HFooladi/molax/compare/v0.1.0...v0.2.0
+[0.1.0]: https://github.com/HFooladi/molax/releases/tag/v0.1.0