[info] Update README.

to squash

Author: Arthur Douillard

README.md

@@ -8,6 +8,16 @@ This repository will store all my implementations of Incremental Learning's pape
 
 Every model must inherit `inclearn.models.base.IncrementalLearner`.
 
+## Papers implemented:
+
+:white_check_mark: --> Paper implemented & reached expected results.\
+:construction: --> Runnable but not yet reached expected results.\
+:x: --> Not yet implemented or barely working.\
+
+[1]: :white_check_mark: iCaRL\
+[2]: :construction: LwF\
+[3]: :construction: End-to-End Incremental Learning\
+
 
 ## iCaRL
 
@@ -26,3 +36,60 @@ The metric used is the `average incremental accuracy`:
 If I understood well, the accuracy at task i (computed on all seen tasks) is averaged
 with all previous accuracy. A bit weird, but doing so get me a curve very similar
 to what the papier displayed.
+
+---
+
+# References
+
+[1] iCaRL:
+
+```
+@InProceedings{icarl,
+author = {Rebuffi, Sylvestre-Alvise and Kolesnikov, Alexander and Sperl, Georg and Lampert, Christoph H.},
+title = {iCaRL: Incremental Classifier and Representation Learning},
+booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
+month = {July},
+year = {2017}
+}
+```
+
+[2]: LwF:
+
+```
+@ARTICLE{lwf,
+author={Z. {Li} and D. {Hoiem}},
+journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
+title={Learning without Forgetting},
+year={2018},
+volume={40},
+number={12},
+pages={2935-2947},
+keywords={convolution;feature extraction;feedforward neural nets;learning (artificial intelligence);fine-tuning adaption techniques;CNN;forgetting method;convolutional neural network;vision system;feature extraction;Feature extraction;Deep learning;Training data;Neural networks;Convolutional neural networks;Knowledge engineering;Learning systems;Visual perception;Convolutional neural networks;transfer learning;multi-task learning;deep learning;visual recognition},
+doi={10.1109/TPAMI.2017.2773081},
+ISSN={0162-8828},
+month={Dec},}
+```
+
+[3]: End-to-End Incremental Learning:
+
+```
+@inproceedings{end_to_end_inc_learn,
+  TITLE = {{End-to-End Incremental Learning}},
+  AUTHOR = {Castro, Francisco M. and Mar{\'i}n-Jim{\'e}nez, Manuel J and Guil, Nicol{\'a}s and Schmid, Cordelia and Alahari, Karteek},
+  URL = {https://hal.inria.fr/hal-01849366},
+  BOOKTITLE = {{ECCV 2018 - European Conference on Computer Vision}},
+  ADDRESS = {Munich, Germany},
+  EDITOR = {Vittorio Ferrari and Martial Hebert and Cristian Sminchisescu and Yair Weiss},
+  PUBLISHER = {{Springer}},
+  SERIES = {Lecture Notes in Computer Science},
+  VOLUME = {11216},
+  PAGES = {241-257},
+  YEAR = {2018},
+  MONTH = Sep,
+  DOI = {10.1007/978-3-030-01258-8\_15},
+  KEYWORDS = {Incremental learning ; CNN ; Distillation loss ; Image classification},
+  PDF = {https://hal.inria.fr/hal-01849366/file/IncrementalLearning_ECCV2018.pdf},
+  HAL_ID = {hal-01849366},
+  HAL_VERSION = {v1},
+}
+```