From c927abe4379b796ec67cf9cc225833a256076737 Mon Sep 17 00:00:00 2001
From: Jaron Kent-Dobias <jaron@kent-dobias.com>
Date: Mon, 1 Sep 2025 08:15:24 -0300
Subject: Many changes

---
 zif.bib | 43 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 43 insertions(+)

(limited to 'zif.bib')

diff --git a/zif.bib b/zif.bib
index d45b279..2f1eabe 100644
--- a/zif.bib
+++ b/zif.bib
@@ -83,3 +83,46 @@
  issn = {2542-4653}
 }
 
+@article{Suryadevara_2024_The,
+ author = {Suryadevara, Praharsh and Casiulis, Mathias and Martiniani, Stefano},
+ title = {The Basins of Attraction of Soft Sphere Packings Are Not Fractal},
+ year = {2024},
+ month = {sep},
+ url = {http://arxiv.org/abs/2409.12113v2},
+ date = {2024-09-18T16:32:49Z},
+ eprint = {2409.12113v2},
+ eprintclass = {cond-mat.stat-mech},
+ eprinttype = {arxiv},
+ urldate = {2025-07-23T12:20:26.278408Z}
+}
+
+@inproceedings{Draxler_2018_Essentially,
+ author = {Draxler, Felix and Veschgini, Kambis and Salmhofer, Manfred and Hamprecht, Fred},
+ title = {Essentially No Barriers in Neural Network Energy Landscape},
+ publisher = {PMLR},
+ year = {2018},
+ month = {10--15 Jul},
+ volume = {80},
+ pages = {1309--1318},
+ url = {https://proceedings.mlr.press/v80/draxler18a.html},
+ abstract = {Training neural networks involves finding minima of a high-dimensional non-convex loss function. Relaxing from linear interpolations, we construct continuous paths between minima of recent neural network architectures on CIFAR10 and CIFAR100. Surprisingly, the paths are essentially flat in both the training and test landscapes. This implies that minima are perhaps best seen as points on a single connected manifold of low loss, rather than as the bottoms of distinct valleys.},
+ booktitle = {Proceedings of the 35th International Conference on Machine Learning},
+ editor = {Dy, Jennifer and Krause, Andreas},
+ pdf = {http://proceedings.mlr.press/v80/draxler18a/draxler18a.pdf},
+ series = {Proceedings of Machine Learning Research}
+}
+
+@article{Liu_2022_Loss,
+ author = {Liu, Chaoyue and Zhu, Libin and Belkin, Mikhail},
+ title = {Loss landscapes and optimization in over-parameterized non-linear systems and neural networks},
+ journal = {Applied and Computational Harmonic Analysis},
+ publisher = {Elsevier BV},
+ year = {2022},
+ month = {July},
+ volume = {59},
+ pages = {85--116},
+ url = {http://dx.doi.org/10.1016/j.acha.2021.12.009},
+ doi = {10.1016/j.acha.2021.12.009},
+ issn = {1063-5203}
+}
+
-- 
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