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.+By+employing+an+asynchronous+denoising+framework+for+different+physical+time+steps%252C+CL-DiffPhyCon+generates+control+signals+conditioned+on+real-time+feedback+from+the+environment+with+significantly+reduced+computational+cost+during+sampling.+Additionally%252C+the+control+process+could+be+further+accelerated+by+incorporating+fast+sampling+techniques%252C+such+as+DDIM.+We+evaluate+CL-DiffPhyCon+on+two+tasks%3a+1D+Burgers%27+equation+control+and+2D+incompressible+fluid+control.+The+results+demonstrate+that+CL-DiffPhyCon+achieves+superior+control+performance+with+significant+improvements+in+sampling+efficiency.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.b2354db7e43439739fe3c12370979a34%3frik%3diWwdwDAZ51lgtQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=What+I+Sdiffusion+Open+and+Diffusion+Closed&FORM=IRPRST&ck=CD522227565CDDCBCCE6C5876828C401&selectedIndex=8&itb=0)
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