[{"data":1,"prerenderedAt":233},["ShallowReactive",2],{"run:lego-res200-30k":3,"run-findings:lego-res200-30k":192},{"run":4,"config":17,"metrics":48,"curve":54,"assets":186},{"id":5,"title":5,"subtitle":6,"eyebrow":7,"date":8,"workspace":9,"commit":10,"tags":11,"verdict":16},"lego-res200-30k","A.12 Resolution scaling 実験 — Lego 200x200 px","Run summary · Phase 5","2026-05-22","splat","59d33f6",[12,13,14,15],"resolution-scaling","lego-30k","res-200","phase-5","partial",[18,21,24,27,30,33,36,39,42,45],{"key":19,"value":20},"dataset","\u002FUsers\u002Fotkrickey\u002Fdev\u002F3dgs-workspace\u002Fdatasets\u002Fnerf_synthetic\u002Flego",{"key":22,"value":23},"iterations","30,000",{"key":25,"value":26},"seed","42",{"key":28,"value":29},"capacity","1,000,000 splats",{"key":31,"value":32},"sh_degree","3",{"key":34,"value":35},"loss","L1Ssim",{"key":37,"value":38},"lambda","0.200",{"key":40,"value":41},"ssim","window=7 sigma=1",{"key":43,"value":44},"backend.backward","Simd",{"key":46,"value":47},"backend.loss_path","Gpu",{"psnr":49,"wallclock":50,"wallclock_regress":51,"splats":52,"final_loss":53},23.901262283325195,"23m 41s",false,80147,"2.477894e-2",{"loss":55,"splats":180},{"iters":56,"values":118},[57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],1,500,1000,1500,2000,2500,3000,3500,4000,4500,5000,5500,6000,6500,7000,7500,8000,8500,9000,9500,10000,10500,11000,11500,12000,12500,13000,13500,14000,14500,15000,15500,16000,16500,17000,17500,18000,18500,19000,19500,20000,20500,21000,21500,22000,22500,23000,23500,24000,24500,25000,25500,26000,26500,27000,27500,28000,28500,29000,29500,30000,[119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179],0.3453391492366791,0.1178787499666214,0.0984860509634018,0.07809743285179138,0.05457461625337601,0.045627448707818985,0.03997416794300079,0.03868171200156212,0.033303152769804,0.03229931741952896,0.03145129978656769,0.031253017485141754,0.03253261372447014,0.029203392565250397,0.03078027442097664,0.028583303093910217,0.028338804841041565,0.030774258077144623,0.02812657132744789,0.026837985962629318,0.026946084573864937,0.02837919071316719,0.026719294488430023,0.027347102761268616,0.02762654982507229,0.025807052850723267,0.027633368968963623,0.025874748826026917,0.02742547169327736,0.02529064007103443,0.025561876595020294,0.025239530950784683,0.025662142783403397,0.02503238432109356,0.025817157700657845,0.024675458669662476,0.025435976684093475,0.02496756985783577,0.02421244978904724,0.02495592087507248,0.024988505989313126,0.02435038983821869,0.025795169174671173,0.024663392454385757,0.024654876440763474,0.024612853303551674,0.023574814200401306,0.024579228833317757,0.025873269885778427,0.02395198494195938,0.024567387998104095,0.02387344092130661,0.023908954113721848,0.024027273058891296,0.023480026051402092,0.024369528517127037,0.023591142147779465,0.02356581948697567,0.02390260621905327,0.02586684748530388,0.02477893978357315,{"iters":181,"values":182},[57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],[183,184,185,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52],5207,5494,21195,{"has_renders":187,"has_splat":51,"render_views":188},true,[189,190,191],"00","01","02",[193],{"id":194,"title":195,"date":8,"status":196,"polarity":197,"category":198,"axes":199,"tags":202,"task_code":210,"related_runs":211,"delta_psnr":228,"delta_wallclock":229,"rank":230,"verdict":16,"impact_summary":231,"detail_path":232},"final-ablation-table","A.5 Final Ablation Table — brush vs 自作 + パラメータ ablation","draft","mixed","tables",[57,200,201],2,3,[15,203,204,205,206,207,208,209,12],"ablation","table","sh-degree","mcmc","multi-scene","brush","cuda","A.5",[212,213,214,215,216,5,217,218,219,220,221,222,223,224,225,226,227],"lego-sh0-30k","lego-sh1-30k","lego-sh2-30k","lego-sh3-30k","lego-mcmc-30k","lego-res400-30k","lego-res800-30k","chair-sh3-30k","ficus-sh3-30k","drums-sh3-30k","hotdog-sh3-30k","m4-brush-bench","c32-brush-bench","c32-orig3dgs-bench","c32-gsplat-smoke","phase5-step31-x-30k","-12.6 dB (自作 24.84 vs brush 37.46)","brush は自作の 0.39× (= 2.59x 速い、同 M4 Max)","high","三層対比 (自作 M4 \u002F brush V100 \u002F CUDA V100) で wgpu→Vulkan が 37.46 dB \u002F 8m24s と CUDA orig (28.4) \u002F gsplat (32.9) より高 PSNR + 高速、自作 24.84 \u002F 23m40s に対し brush wgpu→Metal が 37.40 \u002F 9m08s。「wgpu 抽象は重い」の素朴予想が 2 機種で逆転し、第 2 軸の主張を『抽象コスト \u003C 実装最適化レベル』に再 framing 必須。","\u002Ffindings\u002Ffinal-ablation-table\u002F",1782449788236]