Update news.json

oyb98 · web-flow · commit dc97e44ac04d · 2025-05-04T12:15:40.000+08:00
diff --git a/src/assets/news.json b/src/assets/news.json
@@ -177,6 +177,6 @@
   },
   {
     "new_time":"2025年5月",
-    "content":"K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting 被ICML 2025（CCF A类）录用。结合库普曼理论与卡尔曼滤波，提出了一种高效的变分自编码器，显著提升了长程时间序列概率预测的精度和效率。"
+    "content":"K²VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting 被ICML 2025（CCF A类）录用。结合库普曼理论与卡尔曼滤波，提出了一种高效的变分自编码器，显著提升了长程时间序列概率预测的精度和效率。"
   }
 ]

Original file line number	Diff line number	Diff line change
`@@ -177,6 +177,6 @@`
`177`	`177`	`},`
`178`	`178`	`{`
`179`	`179`	`"new_time":"2025年5月",`
`180`		`- "content":"K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting 被ICML 2025（CCF A类）录用。结合库普曼理论与卡尔曼滤波，提出了一种高效的变分自编码器，显著提升了长程时间序列概率预测的精度和效率。"`
	`180`	`+ "content":"K²VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting 被ICML 2025（CCF A类）录用。结合库普曼理论与卡尔曼滤波，提出了一种高效的变分自编码器，显著提升了长程时间序列概率预测的精度和效率。"`
`181`	`181`	`}`
`182`	`182`	`]`