From 1df9027cc68aac769ac8d00f1a3e056c66ae2d65 Mon Sep 17 00:00:00 2001
From: Leonid Freidovich <48354528+fleonid@users.noreply.github.com>
Date: Thu, 31 Jul 2025 12:06:04 +0200
Subject: [PATCH 1/2] Create arxiv-2507.22176.json

---
 arxiv-2507.22176.json | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 arxiv-2507.22176.json

diff --git a/arxiv-2507.22176.json b/arxiv-2507.22176.json
new file mode 100644
index 0000000..2a4b015
--- /dev/null
+++ b/arxiv-2507.22176.json
@@ -0,0 +1,15 @@
+{
+  "title": "Derivative Estimation from Coarse, Irregular, Noisy Samples: An MLE-Spline Approach",
+  "authors": ["Konstantin E. Avrachenkov", "Leonid B. Freidovich"],
+  "abstract": "We address numerical differentiation under coarse, non-uniform sampling and Gaussian noise. 
+              A maximum-likelihood estimator with L2-norm constraint on a higher-order derivative is obtained, 
+              yielding spline-based solution. We introduce a non-standard parameterization of quadratic splines 
+              and develop recursive online algorithms. Two formulations -- quadratic and zero-order -- offer tradeoff 
+              between smoothness and computational speed. Simulations  demonstrate superior performance over 
+              high-gain observers and super-twisting differentiators under coarse sampling and high noise, 
+              benefiting systems where higher sampling rates are impractical.",
+  "arxiv_id": "2507.22176",
+  "pdf_url": "https://arxiv.org/pdf/2507.22176.pdf",
+  "code_url": "https://github.com/fleonid/MLEdiff",
+  "tasks": ["Numerical Differentiation"]
+}

From 047cbbcb15d08098dd3e69934fb756c9c3bed448 Mon Sep 17 00:00:00 2001
From: Leonid Freidovich <48354528+fleonid@users.noreply.github.com>
Date: Thu, 31 Jul 2025 12:08:14 +0200
Subject: [PATCH 2/2] Update arxiv-2507.22176.json

---
 arxiv-2507.22176.json | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/arxiv-2507.22176.json b/arxiv-2507.22176.json
index 2a4b015..da037cb 100644
--- a/arxiv-2507.22176.json
+++ b/arxiv-2507.22176.json
@@ -1,13 +1,7 @@
 {
   "title": "Derivative Estimation from Coarse, Irregular, Noisy Samples: An MLE-Spline Approach",
   "authors": ["Konstantin E. Avrachenkov", "Leonid B. Freidovich"],
-  "abstract": "We address numerical differentiation under coarse, non-uniform sampling and Gaussian noise. 
-              A maximum-likelihood estimator with L2-norm constraint on a higher-order derivative is obtained, 
-              yielding spline-based solution. We introduce a non-standard parameterization of quadratic splines 
-              and develop recursive online algorithms. Two formulations -- quadratic and zero-order -- offer tradeoff 
-              between smoothness and computational speed. Simulations  demonstrate superior performance over 
-              high-gain observers and super-twisting differentiators under coarse sampling and high noise, 
-              benefiting systems where higher sampling rates are impractical.",
+  "abstract": "We address numerical differentiation under coarse, non-uniform sampling and Gaussian noise. A maximum-likelihood estimator with L2-norm constraint on a higher-order derivative is obtained, yielding spline-based solution. We introduce a non-standard parameterization of quadratic splines and develop recursive online algorithms. Two formulations -- quadratic and zero-order -- offer tradeoff between smoothness and computational speed. Simulations  demonstrate superior performance over high-gain observers and super-twisting differentiators under coarse sampling and high noise, benefiting systems where higher sampling rates are impractical.",
   "arxiv_id": "2507.22176",
   "pdf_url": "https://arxiv.org/pdf/2507.22176.pdf",
   "code_url": "https://github.com/fleonid/MLEdiff",